{"id":3555,"date":"2019-06-14T23:41:21","date_gmt":"2019-06-15T03:41:21","guid":{"rendered":"http:\/\/localhost\/wordpress\/?page_id=3555"},"modified":"2019-06-17T16:23:57","modified_gmt":"2019-06-17T20:23:57","slug":"pubs","status":"publish","type":"page","link":"https:\/\/platial.science\/pubs\/","title":{"rendered":"Publications"},"content":{"rendered":"<div class=\"teachpress_pub_list\"><form name=\"tppublistform\" method=\"get\"><a name=\"tppubs\" id=\"tppubs\"><\/a><\/form><div class=\"tablenav\"><div class=\"tablenav-pages\"><span class=\"displaying-num\">68 entries<\/span> <a class=\"page-numbers button disabled\">&laquo;<\/a> <a class=\"page-numbers button disabled\">&lsaquo;<\/a> 1 of 2 <a href=\"https:\/\/platial.science\/pubs\/?limit=2&amp;tgid=&amp;yr=&amp;type=&amp;usr=&amp;auth=&amp;tsr=#tppubs\" title=\"next page\" class=\"page-numbers button\">&rsaquo;<\/a> <a href=\"https:\/\/platial.science\/pubs\/?limit=2&amp;tgid=&amp;yr=&amp;type=&amp;usr=&amp;auth=&amp;tsr=#tppubs\" title=\"last page\" class=\"page-numbers button\">&raquo;<\/a> <\/div><\/div><div class=\"teachpress_publication_list\"><h3 class=\"tp_h3\" id=\"tp_h3_2026\">2026<\/h3><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> Zhang, Hongyu;  McKenzie, Grant<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('74','tp_links')\" style=\"cursor:pointer;\">Polarized geoprivacy attitudes on Chinese social media: Evidence from Weibo<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">Digital Geography and Society, <\/span><span class=\"tp_pub_additional_volume\">vol. 10, <\/span><span class=\"tp_pub_additional_pages\">pp. 100170, <\/span><span class=\"tp_pub_additional_year\">2026<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_74\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('74','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_74\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('74','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_74\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('74','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_74\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{Zhang2026,<br \/>\r\ntitle = {Polarized geoprivacy attitudes on Chinese social media: Evidence from Weibo},<br \/>\r\nauthor = {Hongyu Zhang and Grant McKenzie},<br \/>\r\ndoi = {10.1016\/j.diggeo.2026.100170},<br \/>\r\nyear  = {2026},<br \/>\r\ndate = {2026-04-14},<br \/>\r\njournal = {Digital Geography and Society},<br \/>\r\nvolume = {10},<br \/>\r\npages = {100170},<br \/>\r\nabstract = {This study aims to investigate the spatial-temporal patterns and major themes in Weibo users&#039; discussions surrounding the platform&#039;s feature that automatically adds a user&#039;s internet protocol-based location to microblog posts and comments. By analyzing user interactions, this research seeks to uncover how the feature is perceived, what key opinions emerge, and who is most affected. We analyze users&#039; reactions to this implementation based on 59,051 microblogs and 113,175 comments about IP location disclosure collected from March to May 2022 on Weibo.com. Spatial and temporal patterns in the data were first identified. Deep reading was then guided by the output of a Latent Dirichlet allocation (LDA) topic model to extract implicit topics from the discourse. Results indicate that both supporters and opponents of the involuntary location disclosure participated in the discussion, with females more involved than males. Propositions of geoprivacy concerns were also summarized according to the related literature and the online discourse. The ambivalent attitudes of some users revealed the dynamic geoprivacy concerns in the communitarian state. The findings of this study will aid policymakers in understanding public opinions about involuntary location disclosure and help digital platforms implement privacy-aware designs in contemporary China.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('74','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_74\" style=\"display:none;\"><div class=\"tp_abstract_entry\">This study aims to investigate the spatial-temporal patterns and major themes in Weibo users&#039; discussions surrounding the platform&#039;s feature that automatically adds a user&#039;s internet protocol-based location to microblog posts and comments. By analyzing user interactions, this research seeks to uncover how the feature is perceived, what key opinions emerge, and who is most affected. We analyze users&#039; reactions to this implementation based on 59,051 microblogs and 113,175 comments about IP location disclosure collected from March to May 2022 on Weibo.com. Spatial and temporal patterns in the data were first identified. Deep reading was then guided by the output of a Latent Dirichlet allocation (LDA) topic model to extract implicit topics from the discourse. Results indicate that both supporters and opponents of the involuntary location disclosure participated in the discussion, with females more involved than males. Propositions of geoprivacy concerns were also summarized according to the related literature and the online discourse. The ambivalent attitudes of some users revealed the dynamic geoprivacy concerns in the communitarian state. The findings of this study will aid policymakers in understanding public opinions about involuntary location disclosure and help digital platforms implement privacy-aware designs in contemporary China.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('74','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_74\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1016\/j.diggeo.2026.100170\" title=\"Follow DOI:10.1016\/j.diggeo.2026.100170\" target=\"_blank\">doi:10.1016\/j.diggeo.2026.100170<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('74','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> Verma, Priyanka;  McKenzie, Grant<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('73','tp_links')\" style=\"cursor:pointer;\">When cities look alike but move differently: comparing urban regions using micromobility trip patterns<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">Journal of Location Based Services, <\/span><span class=\"tp_pub_additional_year\">2026<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_73\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('73','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_73\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('73','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_73\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('73','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_73\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{Verma2026,<br \/>\r\ntitle = {When cities look alike but move differently: comparing urban regions using micromobility trip patterns},<br \/>\r\nauthor = {Priyanka Verma and Grant McKenzie},<br \/>\r\nurl = {https:\/\/www.tandfonline.com\/doi\/full\/10.1080\/17489725.2026.2635029},<br \/>\r\ndoi = {10.1080\/17489725.2026.2635029},<br \/>\r\nyear  = {2026},<br \/>\r\ndate = {2026-02-26},<br \/>\r\nurldate = {2026-02-26},<br \/>\r\njournal = {Journal of Location Based Services},<br \/>\r\nabstract = {Regulating free-floating micromobility services, such as e-scooters, presents a unique challenge for cities. This work aims to support cities in developing regulations by assessing similarities between and within urban regions based on micromobility trip patterns, built environment characteristics, and socioeconomic and demographic profiles. We develop three random forest classification models across these dimensions for five U.S. cities \u2013 Baltimore, Denver, Detroit, Portland, and Washington DC. We demonstrate that cities with similar built environment characteristics or socioeconomic and demographic profiles do not always exhibit comparable micromobility characteristics. Similarly, we find that cities exhibit more generalizable micromobility patterns than they do through built environment or socioeconomic and demographics. Our regional similarity models offer a means to compare micromobility across regions, while contrasting how regions differ in their built environment or socioeconomic and demographic characteristics. By enabling micromobility focused comparisons, cities with similar built environment characteristics or socioeconomic and demographic profiles may draw conclusions as to which policies may be most effective.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('73','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_73\" style=\"display:none;\"><div class=\"tp_abstract_entry\">Regulating free-floating micromobility services, such as e-scooters, presents a unique challenge for cities. This work aims to support cities in developing regulations by assessing similarities between and within urban regions based on micromobility trip patterns, built environment characteristics, and socioeconomic and demographic profiles. We develop three random forest classification models across these dimensions for five U.S. cities \u2013 Baltimore, Denver, Detroit, Portland, and Washington DC. We demonstrate that cities with similar built environment characteristics or socioeconomic and demographic profiles do not always exhibit comparable micromobility characteristics. Similarly, we find that cities exhibit more generalizable micromobility patterns than they do through built environment or socioeconomic and demographics. Our regional similarity models offer a means to compare micromobility across regions, while contrasting how regions differ in their built environment or socioeconomic and demographic characteristics. By enabling micromobility focused comparisons, cities with similar built environment characteristics or socioeconomic and demographic profiles may draw conclusions as to which policies may be most effective.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('73','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_73\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-globe\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/www.tandfonline.com\/doi\/full\/10.1080\/17489725.2026.2635029\" title=\"https:\/\/www.tandfonline.com\/doi\/full\/10.1080\/17489725.2026.2635029\" target=\"_blank\">https:\/\/www.tandfonline.com\/doi\/full\/10.1080\/17489725.2026.2635029<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1080\/17489725.2026.2635029\" title=\"Follow DOI:10.1080\/17489725.2026.2635029\" target=\"_blank\">doi:10.1080\/17489725.2026.2635029<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('73','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><h3 class=\"tp_h3\" id=\"tp_h3_2025\">2025<\/h3><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> Qiang, Dan;  McKenzie, Grant<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('72','tp_links')\" style=\"cursor:pointer;\">How events move us: Estimating the causal effects of special events on shared micromobility<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">Journal of Geovisualization and Spatial Analysis, <\/span><span class=\"tp_pub_additional_volume\">vol. 10, <\/span><span class=\"tp_pub_additional_issue\">iss. 1, <\/span><span class=\"tp_pub_additional_year\">2025<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_72\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('72','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_72\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('72','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_72\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('72','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_72\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{nokey,<br \/>\r\ntitle = {How events move us: Estimating the causal effects of special events on shared micromobility},<br \/>\r\nauthor = {Dan Qiang and Grant McKenzie},<br \/>\r\nurl = {http:\/\/grantmckenzie.com\/academics\/Qiang2025b.pdf},<br \/>\r\ndoi = {10.1007\/s41651-025-00244-1},<br \/>\r\nyear  = {2025},<br \/>\r\ndate = {2025-12-05},<br \/>\r\nurldate = {2025-12-05},<br \/>\r\njournal = {Journal of Geovisualization and Spatial Analysis},<br \/>\r\nvolume = {10},<br \/>\r\nissue = {1},<br \/>\r\npublisher = {Springer},<br \/>\r\nabstract = {Special events, such as festivals, parades, and protests, can cause sudden surges or disruptions in travel demand, thereby placing stress on transportation systems. As shared micromobility becomes an increasingly important part of urban transportation, understanding how these events affect its ridership is crucial for ensuring safety, efficiency, and sustainability. In this study, we investigate the causal impacts of various event types by applying Double Machine Learning (DML) to high-resolution shared micromobility trip data (e-bikes and e-scooters) and multi-source event records in Washington, D.C. These events include government-authorized large events, independently organized small events, and government-registered protests. Our results show that many events have far stronger actual influences on shared micromobility than correlational analysis suggests, as confounding factors can mask their actual impact. For instance, festivals show four to seven times greater impact under causal estimation. We also find that the increase in gas prices suppresses discretionary travel, resulting in reduced shared micromobility usage during events. Another key insight is the different demand mechanisms: large events interact with temporal and built environment features to boost ridership, whereas small events are primarily influenced by temporal features, such as event duration and weather, with little influence from infrastructure factors. These findings highlight the need for tailored policies, including infrastructure investment for large events and operational incentives for smaller ones. This research provides a causal foundation for urban mobility planning, supporting the development of more resilient and efficient transportation systems in event-dense urban areas.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('72','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_72\" style=\"display:none;\"><div class=\"tp_abstract_entry\">Special events, such as festivals, parades, and protests, can cause sudden surges or disruptions in travel demand, thereby placing stress on transportation systems. As shared micromobility becomes an increasingly important part of urban transportation, understanding how these events affect its ridership is crucial for ensuring safety, efficiency, and sustainability. In this study, we investigate the causal impacts of various event types by applying Double Machine Learning (DML) to high-resolution shared micromobility trip data (e-bikes and e-scooters) and multi-source event records in Washington, D.C. These events include government-authorized large events, independently organized small events, and government-registered protests. Our results show that many events have far stronger actual influences on shared micromobility than correlational analysis suggests, as confounding factors can mask their actual impact. For instance, festivals show four to seven times greater impact under causal estimation. We also find that the increase in gas prices suppresses discretionary travel, resulting in reduced shared micromobility usage during events. Another key insight is the different demand mechanisms: large events interact with temporal and built environment features to boost ridership, whereas small events are primarily influenced by temporal features, such as event duration and weather, with little influence from infrastructure factors. These findings highlight the need for tailored policies, including infrastructure investment for large events and operational incentives for smaller ones. This research provides a causal foundation for urban mobility planning, supporting the development of more resilient and efficient transportation systems in event-dense urban areas.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('72','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_72\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-file-pdf\"><\/i><a class=\"tp_pub_list\" href=\"http:\/\/grantmckenzie.com\/academics\/Qiang2025b.pdf\" title=\"http:\/\/grantmckenzie.com\/academics\/Qiang2025b.pdf\" target=\"_blank\">http:\/\/grantmckenzie.com\/academics\/Qiang2025b.pdf<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1007\/s41651-025-00244-1\" title=\"Follow DOI:10.1007\/s41651-025-00244-1\" target=\"_blank\">doi:10.1007\/s41651-025-00244-1<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('72','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> Romm, Daniel;  Kinman, Lexi;  Manaugh, Kevin;  McKenzie, Grant<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('70','tp_links')\" style=\"cursor:pointer;\">Measuring and Moving on the Street: A Scoping Review of Street Space Allocation Studies<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">International Journal of Sustainable Transportation, <\/span><span class=\"tp_pub_additional_year\">2025<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_70\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('70','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_70\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('70','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_70\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('70','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_70\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{Romm2025b,<br \/>\r\ntitle = {Measuring and Moving on the Street: A Scoping Review of Street Space Allocation Studies},<br \/>\r\nauthor = {Daniel Romm and Lexi Kinman and Kevin Manaugh and Grant McKenzie},<br \/>\r\nurl = {http:\/\/grantmckenzie.com\/academics\/Romm2025b.pdf},<br \/>\r\ndoi = {10.1080\/15568318.2025.2570322},<br \/>\r\nyear  = {2025},<br \/>\r\ndate = {2025-10-22},<br \/>\r\nurldate = {2025-10-22},<br \/>\r\njournal = {International Journal of Sustainable Transportation},<br \/>\r\nabstract = {A field of research is emerging that examines the allocation of street space to different transportation infrastructures, set in the context of a growing recognition of the need to redesign city streets away from the dominance that cars have held over city streets for the past century. In this scoping review, we systematically search the literature to identify 12 peer-reviewed journal articles that use spatial analysis methods to study street space allocation to transportation modes, synthesizing and reflecting on the studies\u2019 methodologies, results, and identified policy implications and future research areas. From this synthesis, key themes emerge around how the studies frame their work in the transportation justice literature and towards conceptualizing an equitable streetscape, the differences in the methodologies employed and promising avenues to improve their methods, and the difficulties in comparing results across studies. Stemming from the reviewed studies, this review offers several directions for future research to encourage the development of street space allocation research, a field well-positioned to contribute to research and policy around critiquing and improving city streets and urban liveability.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('70','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_70\" style=\"display:none;\"><div class=\"tp_abstract_entry\">A field of research is emerging that examines the allocation of street space to different transportation infrastructures, set in the context of a growing recognition of the need to redesign city streets away from the dominance that cars have held over city streets for the past century. In this scoping review, we systematically search the literature to identify 12 peer-reviewed journal articles that use spatial analysis methods to study street space allocation to transportation modes, synthesizing and reflecting on the studies\u2019 methodologies, results, and identified policy implications and future research areas. From this synthesis, key themes emerge around how the studies frame their work in the transportation justice literature and towards conceptualizing an equitable streetscape, the differences in the methodologies employed and promising avenues to improve their methods, and the difficulties in comparing results across studies. Stemming from the reviewed studies, this review offers several directions for future research to encourage the development of street space allocation research, a field well-positioned to contribute to research and policy around critiquing and improving city streets and urban liveability.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('70','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_70\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-file-pdf\"><\/i><a class=\"tp_pub_list\" href=\"http:\/\/grantmckenzie.com\/academics\/Romm2025b.pdf\" title=\"http:\/\/grantmckenzie.com\/academics\/Romm2025b.pdf\" target=\"_blank\">http:\/\/grantmckenzie.com\/academics\/Romm2025b.pdf<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1080\/15568318.2025.2570322\" title=\"Follow DOI:10.1080\/15568318.2025.2570322\" target=\"_blank\">doi:10.1080\/15568318.2025.2570322<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('70','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_inbook\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> McKenzie, Grant;  Janowicz, Krzysztof;  Kessler, Carsten<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('71','tp_links')\" style=\"cursor:pointer;\">Trust in foundation models and GenAI: A geographic perspective<\/a> <span class=\"tp_pub_type tp_  inbook\">Book Chapter<\/span> <span class=\"tp_pub_label_status forthcoming\">Forthcoming<\/span><\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span>Cai Janowicz, L. (Ed.): <span class=\"tp_pub_additional_booktitle\">Geography according to ChatGPT, <\/span><span class=\"tp_pub_additional_publisher\">Sage Press, <\/span>Forthcoming.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_71\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('71','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_71\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('71','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_71\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('71','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_71\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@inbook{McKenzie2025c,<br \/>\r\ntitle = {Trust in foundation models and GenAI: A geographic perspective},<br \/>\r\nauthor = {Grant McKenzie and Krzysztof Janowicz and Carsten Kessler},<br \/>\r\neditor = {Janowicz, Cai, L., Mai, G., Bennett, L., Zhu, R., Gao, S., Hu, Y., Wang, Z.},<br \/>\r\nurl = {https:\/\/arxiv.org\/abs\/2510.17942},<br \/>\r\nyear  = {2025},<br \/>\r\ndate = {2025-10-21},<br \/>\r\nbooktitle = {Geography according to ChatGPT},<br \/>\r\npublisher = {Sage Press},<br \/>\r\nabstract = {Large-scale pre-trained machine learning models have reshaped our understanding of artificial intelligence across numerous domains, including our own field of geography. As with any new technology, trust has taken on an important role in this discussion. In this chapter, we examine the multifaceted concept of trust in foundation models, particularly within a geographic context. As reliance on these models increases and they become relied upon for critical decision-making, trust, while essential, has become a fractured concept. Here we categorize trust into three types: epistemic trust in the training data, operational trust in the model&#039;s functionality, and interpersonal trust in the model developers. Each type of trust brings with it unique implications for geographic applications. Topics such as cultural context, data heterogeneity, and spatial relationships are fundamental to the spatial sciences and play an important role in developing trust. The chapter continues with a discussion of the challenges posed by different forms of biases, the importance of transparency and explainability, and ethical responsibilities in model development. Finally, the novel perspective of geographic information scientists is emphasized with a call for further transparency, bias mitigation, and regionally-informed policies. Simply put, this chapter aims to provide a conceptual starting point for researchers, practitioners, and policy-makers to better understand trust in (generative) GeoAI.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {forthcoming},<br \/>\r\ntppubtype = {inbook}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('71','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_71\" style=\"display:none;\"><div class=\"tp_abstract_entry\">Large-scale pre-trained machine learning models have reshaped our understanding of artificial intelligence across numerous domains, including our own field of geography. As with any new technology, trust has taken on an important role in this discussion. In this chapter, we examine the multifaceted concept of trust in foundation models, particularly within a geographic context. As reliance on these models increases and they become relied upon for critical decision-making, trust, while essential, has become a fractured concept. Here we categorize trust into three types: epistemic trust in the training data, operational trust in the model&#039;s functionality, and interpersonal trust in the model developers. Each type of trust brings with it unique implications for geographic applications. Topics such as cultural context, data heterogeneity, and spatial relationships are fundamental to the spatial sciences and play an important role in developing trust. The chapter continues with a discussion of the challenges posed by different forms of biases, the importance of transparency and explainability, and ethical responsibilities in model development. Finally, the novel perspective of geographic information scientists is emphasized with a call for further transparency, bias mitigation, and regionally-informed policies. Simply put, this chapter aims to provide a conceptual starting point for researchers, practitioners, and policy-makers to better understand trust in (generative) GeoAI.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('71','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_71\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"ai ai-arxiv\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/arxiv.org\/abs\/2510.17942\" title=\"https:\/\/arxiv.org\/abs\/2510.17942\" target=\"_blank\">https:\/\/arxiv.org\/abs\/2510.17942<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('71','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_inproceedings\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> McKenzie, Grant<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('68','tp_links')\" style=\"cursor:pointer;\">MODAP: A Multi-City Open Data &amp; Analytics Platform for Micromobility Research<\/a> <span class=\"tp_pub_type tp_  inproceedings\">Proceedings Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_booktitle\">Proceedings of the Thirteenth International Conference on Geographic Information Science (GIScience 2025), <\/span><span class=\"tp_pub_additional_pages\">pp. 6:1-6:14, <\/span><span class=\"tp_pub_additional_publisher\">Schloss Dagstuhl \u2013 Leibniz-Zentrum f\u00fcr Informatik, <\/span><span class=\"tp_pub_additional_year\">2025<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_68\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('68','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_68\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('68','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_68\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('68','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_68\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@inproceedings{McKenzie2025b,<br \/>\r\ntitle = {MODAP: A Multi-City Open Data & Analytics Platform for Micromobility Research},<br \/>\r\nauthor = {Grant McKenzie},<br \/>\r\nurl = {https:\/\/drops.dagstuhl.de\/entities\/document\/10.4230\/LIPIcs.GIScience.2025.6},<br \/>\r\ndoi = {10.4230\/LIPIcs.GIScience.2025.6},<br \/>\r\nyear  = {2025},<br \/>\r\ndate = {2025-08-15},<br \/>\r\nurldate = {2025-08-15},<br \/>\r\nbooktitle = {Proceedings of the Thirteenth International Conference on Geographic Information Science (GIScience 2025)},<br \/>\r\nvolume = {346},<br \/>\r\npages = {6:1-6:14},<br \/>\r\npublisher = {Schloss Dagstuhl \u2013 Leibniz-Zentrum f\u00fcr Informatik},<br \/>\r\nseries = {Leibniz International Proceedings in Informatics (LIPIcs)},<br \/>\r\nabstract = {Over the past decade, micromobility services, particularly electric vehicles for personal short-distance trips, have experienced significant growth. Major cities around the world now host extensive fleets of vehicles available for short-term public rental. While previous research has examined usage patterns within and between a few select cities, large, open, and publicly accessible data sets for analyzing mobility across multiple cities are extremely limited.  We have collected, curated, and aggregated over twenty million e-scooter and e-bicycle trips across five major cities and are openly releasing these data for use by mobility and sustainable transport researchers, urban planners, and policymakers. To accompany these data, we developed modap (Micromobility Open Data & Analytics Platform), a geovisual analytics tool that empowers researchers to explore the temporal and regional patterns of e-mobility trips within our open data set and download the data for offline analysis. Our objective is to foster further research into city-scale mobility patterns and to equip researchers, community members, and policymakers with the necessary tools to conduct this work.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {inproceedings}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('68','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_68\" style=\"display:none;\"><div class=\"tp_abstract_entry\">Over the past decade, micromobility services, particularly electric vehicles for personal short-distance trips, have experienced significant growth. Major cities around the world now host extensive fleets of vehicles available for short-term public rental. While previous research has examined usage patterns within and between a few select cities, large, open, and publicly accessible data sets for analyzing mobility across multiple cities are extremely limited.  We have collected, curated, and aggregated over twenty million e-scooter and e-bicycle trips across five major cities and are openly releasing these data for use by mobility and sustainable transport researchers, urban planners, and policymakers. To accompany these data, we developed modap (Micromobility Open Data &amp; Analytics Platform), a geovisual analytics tool that empowers researchers to explore the temporal and regional patterns of e-mobility trips within our open data set and download the data for offline analysis. Our objective is to foster further research into city-scale mobility patterns and to equip researchers, community members, and policymakers with the necessary tools to conduct this work.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('68','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_68\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-globe\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/drops.dagstuhl.de\/entities\/document\/10.4230\/LIPIcs.GIScience.2025.6\" title=\"https:\/\/drops.dagstuhl.de\/entities\/document\/10.4230\/LIPIcs.GIScience.2025.6\" target=\"_blank\">https:\/\/drops.dagstuhl.de\/entities\/document\/10.4230\/LIPIcs.GIScience.2025.6<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.4230\/LIPIcs.GIScience.2025.6\" title=\"Follow DOI:10.4230\/LIPIcs.GIScience.2025.6\" target=\"_blank\">doi:10.4230\/LIPIcs.GIScience.2025.6<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('68','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_inproceedings\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> Zhang, Hongyu;  McKenzie, Grant<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('67','tp_links')\" style=\"cursor:pointer;\">Evaluating Spatial Dependency in Regional Similarities of the Population Dynamics Foundation Model<\/a> <span class=\"tp_pub_type tp_  inproceedings\">Proceedings Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_booktitle\">Proceedings of the 28th Annual Meeting of the Association of Geographic Information Laboratories in Europe, <\/span><span class=\"tp_pub_additional_year\">2025<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_resource_link\"><a id=\"tp_links_sh_67\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('67','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_67\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('67','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_67\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@inproceedings{Zhang2025,<br \/>\r\ntitle = {Evaluating Spatial Dependency in Regional Similarities of the Population Dynamics Foundation Model},<br \/>\r\nauthor = {Hongyu Zhang and Grant McKenzie},<br \/>\r\nurl = {https:\/\/grantmckenzie.com\/academics\/Zhang_AGILE2025.pdf},<br \/>\r\nyear  = {2025},<br \/>\r\ndate = {2025-06-10},<br \/>\r\nurldate = {2025-06-10},<br \/>\r\nbooktitle = {Proceedings of the 28th Annual Meeting of the Association of Geographic Information Laboratories in Europe},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {inproceedings}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('67','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_67\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-file-pdf\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/grantmckenzie.com\/academics\/Zhang_AGILE2025.pdf\" title=\"https:\/\/grantmckenzie.com\/academics\/Zhang_AGILE2025.pdf\" target=\"_blank\">https:\/\/grantmckenzie.com\/academics\/Zhang_AGILE2025.pdf<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('67','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_inproceedings\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> Qiang, Dan;  McKenzie, Grant<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('66','tp_links')\" style=\"cursor:pointer;\">Mobility Vitality: Measuring urban vitality through active and micro-mobility modes.<\/a> <span class=\"tp_pub_type tp_  inproceedings\">Proceedings Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_booktitle\">Proceedings of the 28th Association of Geographic Information Laboratories in Europe Conference (AGILE 2025), <\/span><span class=\"tp_pub_additional_publisher\">AGILE GIScience Series, <\/span><span class=\"tp_pub_additional_year\">2025<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_66\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('66','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_66\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('66','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_66\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('66','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_66\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@inproceedings{Qiang2025,<br \/>\r\ntitle = {Mobility Vitality: Measuring urban vitality through active and micro-mobility modes.},<br \/>\r\nauthor = {Dan Qiang and Grant McKenzie},<br \/>\r\nurl = {https:\/\/www.grantmckenzie.com\/academics\/AGILE2025_Mobility_Vitality.pdf},<br \/>\r\ndoi = {10.5194\/agile-giss-6-9-2025},<br \/>\r\nyear  = {2025},<br \/>\r\ndate = {2025-06-09},<br \/>\r\nurldate = {2025-06-10},<br \/>\r\nbooktitle = {Proceedings of the 28th Association of Geographic Information Laboratories in Europe Conference (AGILE 2025)},<br \/>\r\nvolume = {6},<br \/>\r\npublisher = {AGILE GIScience Series},<br \/>\r\nabstract = {Urban vitality captures the dynamic and interactive nature of city environments by highlighting how residents engage with public spaces, making it essential for differentiating neighborhoods. Traditional indicators focused on static measures, such as density, land-use diversity, and built environment design. Most of these measures fail to capture the dynamic nature of vitality. This paper introduces the concept of Mobility Vitality, a novel measure that captures the dynamic and vibrant nature of human activities through the analysis of active and micro-mobility modes, including biking, e-scootering, and recreational running. Taking Washington, D.C. as a case study, we analyze the spatiotemporal patterns of mobility across different modes and time periods, revealing significant variations in mobility patterns between the downtown core and peripheral areas. The results also indicate that the most unique time series of the three micro-mobility modes are weekend mornings and weekday nights, and fluctuations are more pronounced within a day than between weekdays and weekends. The proposed analysis framework may guide infrastructure investments, optimize urban transport networks, and advance more equitable and sustainable cities.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {inproceedings}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('66','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_66\" style=\"display:none;\"><div class=\"tp_abstract_entry\">Urban vitality captures the dynamic and interactive nature of city environments by highlighting how residents engage with public spaces, making it essential for differentiating neighborhoods. Traditional indicators focused on static measures, such as density, land-use diversity, and built environment design. Most of these measures fail to capture the dynamic nature of vitality. This paper introduces the concept of Mobility Vitality, a novel measure that captures the dynamic and vibrant nature of human activities through the analysis of active and micro-mobility modes, including biking, e-scootering, and recreational running. Taking Washington, D.C. as a case study, we analyze the spatiotemporal patterns of mobility across different modes and time periods, revealing significant variations in mobility patterns between the downtown core and peripheral areas. The results also indicate that the most unique time series of the three micro-mobility modes are weekend mornings and weekday nights, and fluctuations are more pronounced within a day than between weekdays and weekends. The proposed analysis framework may guide infrastructure investments, optimize urban transport networks, and advance more equitable and sustainable cities.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('66','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_66\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-file-pdf\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/www.grantmckenzie.com\/academics\/AGILE2025_Mobility_Vitality.pdf\" title=\"https:\/\/www.grantmckenzie.com\/academics\/AGILE2025_Mobility_Vitality.pdf\" target=\"_blank\">https:\/\/www.grantmckenzie.com\/academics\/AGILE2025_Mobility_Vitality.pdf<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.5194\/agile-giss-6-9-2025\" title=\"Follow DOI:10.5194\/agile-giss-6-9-2025\" target=\"_blank\">doi:10.5194\/agile-giss-6-9-2025<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('66','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> Romm, Daniel;  Chavez, Jose Arturo Jasso;  Kinman, Lexi;  Salsabilian, Pegah;  McKenzie, Grant;  Manaugh, Kevin<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('69','tp_links')\" style=\"cursor:pointer;\">The Cars are Going to be Alright: Examining Micromobility Infrastructure Space Allocation and Potential Improvement Scenarios in Montr\u00e9al<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">Journal of Cycling and Micromobility Research, <\/span><span class=\"tp_pub_additional_number\">no. 100071, <\/span><span class=\"tp_pub_additional_year\">2025<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_69\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('69','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_69\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('69','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_69\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('69','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_69\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{Romm2025,<br \/>\r\ntitle = {The Cars are Going to be Alright: Examining Micromobility Infrastructure Space Allocation and Potential Improvement Scenarios in Montr\u00e9al},<br \/>\r\nauthor = {Daniel Romm and Jose Arturo Jasso Chavez and Lexi Kinman and Pegah Salsabilian and Grant McKenzie and Kevin Manaugh},<br \/>\r\ndoi = {10.1016\/j.jcmr.2025.100071},<br \/>\r\nyear  = {2025},<br \/>\r\ndate = {2025-06-07},<br \/>\r\nurldate = {2025-06-03},<br \/>\r\njournal = {Journal of Cycling and Micromobility Research},<br \/>\r\nnumber = {100071},<br \/>\r\nabstract = {Many cities today are redesigning their streetscapes to redress the historical privilege afforded to the automobile in planning and policy. Much streetscape redesign is around transport infrastructure space, which largely prioritizes car travel and marginalizes other travel modes. Attempts by planners and policy makers to this end often are met with public opposition by advocates of the car, protesting about losing space on the street. This is empirically investigated with the case of Montr\u00e9al by determining the allocation of street space to transport infrastructures, deriving measures of infrastructure space per traveller, and devising an Equal Infrastructure Allocation score to measure the imbalance between infrastructure provision per travel mode. Per borough, the distribution of transport infrastructure is examined, alongside correlations with demographic, socio-economic, land use, and crash rate variables. Potential scenarios of significant micromobility infrastructure improvement are modelled to test how infrastructure space apportionment per mode changes. This investigation discovers that even large improvements to micromobility infrastructure have a minor effect on space allocated to automobiles. Equal Infrastructure Allocation score and associated indicators are presented as useful tools for planners and policy makers implementing micromobility infrastructure projects, to better communicate with the public and address potential opposition.  },<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('69','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_69\" style=\"display:none;\"><div class=\"tp_abstract_entry\">Many cities today are redesigning their streetscapes to redress the historical privilege afforded to the automobile in planning and policy. Much streetscape redesign is around transport infrastructure space, which largely prioritizes car travel and marginalizes other travel modes. Attempts by planners and policy makers to this end often are met with public opposition by advocates of the car, protesting about losing space on the street. This is empirically investigated with the case of Montr\u00e9al by determining the allocation of street space to transport infrastructures, deriving measures of infrastructure space per traveller, and devising an Equal Infrastructure Allocation score to measure the imbalance between infrastructure provision per travel mode. Per borough, the distribution of transport infrastructure is examined, alongside correlations with demographic, socio-economic, land use, and crash rate variables. Potential scenarios of significant micromobility infrastructure improvement are modelled to test how infrastructure space apportionment per mode changes. This investigation discovers that even large improvements to micromobility infrastructure have a minor effect on space allocated to automobiles. Equal Infrastructure Allocation score and associated indicators are presented as useful tools for planners and policy makers implementing micromobility infrastructure projects, to better communicate with the public and address potential opposition.  <\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('69','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_69\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1016\/j.jcmr.2025.100071\" title=\"Follow DOI:10.1016\/j.jcmr.2025.100071\" target=\"_blank\">doi:10.1016\/j.jcmr.2025.100071<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('69','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> McKenzie, Grant;  Romm, Daniel;  F\u00e9r\u00e9, Clara;  Balarezo, Maria Laura Guerrero<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('65','tp_links')\" style=\"cursor:pointer;\">Gender differences in urban recreational running: A data-driven approach<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">Journal of Transport Geography, <\/span><span class=\"tp_pub_additional_volume\">vol. 124, <\/span><span class=\"tp_pub_additional_number\">no. 104171, <\/span><span class=\"tp_pub_additional_year\">2025<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_65\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('65','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_65\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('65','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_65\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('65','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_65\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{McKenzie2025,<br \/>\r\ntitle = {Gender differences in urban recreational running: A data-driven approach},<br \/>\r\nauthor = {Grant McKenzie and Daniel Romm and Clara F\u00e9r\u00e9 and Maria Laura Guerrero Balarezo},<br \/>\r\nurl = {https:\/\/grantmckenzie.com\/academics\/McKenzie2025_01.pdf<br \/>\r\nhttps:\/\/www.sciencedirect.com\/science\/article\/pii\/S0966692325000626},<br \/>\r\ndoi = {10.1016\/j.jtrangeo.2025.104171},<br \/>\r\nyear  = {2025},<br \/>\r\ndate = {2025-03-04},<br \/>\r\nurldate = {2025-02-24},<br \/>\r\njournal = {Journal of Transport Geography},<br \/>\r\nvolume = {124},<br \/>\r\nnumber = {104171},<br \/>\r\nabstract = {Exploring the dynamics of urban recreational running, this study examines the spatial and temporal patterns of running activities among men and women in two major North American cities. Using geosocial fitness tracking data, we identify distinct gender-based preferences in terms of location and time, highlighting significant variations between the two cities and shifts between day and night running habits.  We further investigate the influence of socio-economic, demographic, and built environment factors on these different spatiotemporal patterns. Insights from this work are important for urban planners and public health officials, providing a data-driven foundation for developing more inclusive and safe public spaces for recreational activities. The study not only contributes to our understanding of urban recreational behaviors but also addresses broader societal concerns about gender and public space utilization.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('65','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_65\" style=\"display:none;\"><div class=\"tp_abstract_entry\">Exploring the dynamics of urban recreational running, this study examines the spatial and temporal patterns of running activities among men and women in two major North American cities. Using geosocial fitness tracking data, we identify distinct gender-based preferences in terms of location and time, highlighting significant variations between the two cities and shifts between day and night running habits.  We further investigate the influence of socio-economic, demographic, and built environment factors on these different spatiotemporal patterns. Insights from this work are important for urban planners and public health officials, providing a data-driven foundation for developing more inclusive and safe public spaces for recreational activities. The study not only contributes to our understanding of urban recreational behaviors but also addresses broader societal concerns about gender and public space utilization.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('65','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_65\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-file-pdf\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/grantmckenzie.com\/academics\/McKenzie2025_01.pdf\" title=\"https:\/\/grantmckenzie.com\/academics\/McKenzie2025_01.pdf\" target=\"_blank\">https:\/\/grantmckenzie.com\/academics\/McKenzie2025_01.pdf<\/a><\/li><li><i class=\"fas fa-globe\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0966692325000626\" title=\"https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0966692325000626\" target=\"_blank\">https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0966692325000626<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1016\/j.jtrangeo.2025.104171\" title=\"Follow DOI:10.1016\/j.jtrangeo.2025.104171\" target=\"_blank\">doi:10.1016\/j.jtrangeo.2025.104171<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('65','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><h3 class=\"tp_h3\" id=\"tp_h3_2024\">2024<\/h3><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> Zhang, Hongyu;  McKenzie, Grant<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('64','tp_links')\" style=\"cursor:pointer;\">Geoprivacy knowledge, attitudes, and behaviours in contemporary China<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">Geographical Review, <\/span><span class=\"tp_pub_additional_year\">2024<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_64\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('64','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_64\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('64','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_64\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('64','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_64\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{Zhang2024,<br \/>\r\ntitle = {Geoprivacy knowledge, attitudes, and behaviours in contemporary China},<br \/>\r\nauthor = {Hongyu Zhang and Grant McKenzie},<br \/>\r\nurl = {https:\/\/grantmckenzie.com\/academics\/Zhang2024.pdf<br \/>\r\nhttps:\/\/www.tandfonline.com\/doi\/full\/10.1080\/00167428.2024.2422873},<br \/>\r\ndoi = {10.1080\/00167428.2024.2422873},<br \/>\r\nyear  = {2024},<br \/>\r\ndate = {2024-11-14},<br \/>\r\nurldate = {2024-11-14},<br \/>\r\njournal = {Geographical Review},<br \/>\r\npublisher = {Taylor & Francis},<br \/>\r\nabstract = {China has an internet penetration rate of over 70% and a massive user base of social media. However, the topic of privacy attitudes among Chinese individuals remains understudied. We analyzed geoprivacy concerns in China through an online survey and regression analysis. Our findings suggest a positive relation among privacy knowledge, attitude, and behaviour, consistent with related literature. Declarative knowledge (e.g., privacy rights), on the other hand, was found to have a negative relation with privacy concerns, which has not been reported previously. In terms of demographic moderators, females had less privacy knowledge but more privacy protection behaviours, while the impact of age on privacy concerns was inconclusive. A notable discovery was the regional difference in privacy concerns within China, suggesting the potential geopolitical influence on individuals' values and beliefs. Combined with the uncovering of behavioural change in response to involuntary location disclosure, the results of this article challenge the conventional notion that Chinese individuals are indifferent to their online privacy, thus re-introducing an under-explored perspective from the global south into geoprivacy studies. },<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('64','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_64\" style=\"display:none;\"><div class=\"tp_abstract_entry\">China has an internet penetration rate of over 70% and a massive user base of social media. However, the topic of privacy attitudes among Chinese individuals remains understudied. We analyzed geoprivacy concerns in China through an online survey and regression analysis. Our findings suggest a positive relation among privacy knowledge, attitude, and behaviour, consistent with related literature. Declarative knowledge (e.g., privacy rights), on the other hand, was found to have a negative relation with privacy concerns, which has not been reported previously. In terms of demographic moderators, females had less privacy knowledge but more privacy protection behaviours, while the impact of age on privacy concerns was inconclusive. A notable discovery was the regional difference in privacy concerns within China, suggesting the potential geopolitical influence on individuals' values and beliefs. Combined with the uncovering of behavioural change in response to involuntary location disclosure, the results of this article challenge the conventional notion that Chinese individuals are indifferent to their online privacy, thus re-introducing an under-explored perspective from the global south into geoprivacy studies. <\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('64','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_64\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-file-pdf\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/grantmckenzie.com\/academics\/Zhang2024.pdf\" title=\"https:\/\/grantmckenzie.com\/academics\/Zhang2024.pdf\" target=\"_blank\">https:\/\/grantmckenzie.com\/academics\/Zhang2024.pdf<\/a><\/li><li><i class=\"fas fa-globe\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/www.tandfonline.com\/doi\/full\/10.1080\/00167428.2024.2422873\" title=\"https:\/\/www.tandfonline.com\/doi\/full\/10.1080\/00167428.2024.2422873\" target=\"_blank\">https:\/\/www.tandfonline.com\/doi\/full\/10.1080\/00167428.2024.2422873<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1080\/00167428.2024.2422873\" title=\"Follow DOI:10.1080\/00167428.2024.2422873\" target=\"_blank\">doi:10.1080\/00167428.2024.2422873<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('64','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> Qiang, Dan;  McKenzie, Grant<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('63','tp_links')\" style=\"cursor:pointer;\">Navigating the Post-Pandemic Urban Landscape: Disparities in Transportation Recovery &amp; Regional Insights from New York City<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">Computers, Environment and Urban Systems, <\/span><span class=\"tp_pub_additional_volume\">vol. 110, <\/span><span class=\"tp_pub_additional_pages\">pp. 102111, <\/span><span class=\"tp_pub_additional_year\">2024<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_63\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('63','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_63\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('63','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_63\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('63','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_63\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{nokey,<br \/>\r\ntitle = {Navigating the Post-Pandemic Urban Landscape: Disparities in Transportation Recovery & Regional Insights from New York City},<br \/>\r\nauthor = {Dan Qiang and Grant McKenzie},<br \/>\r\nurl = {https:\/\/grantmckenzie.com\/academics\/Qiang_2024.pdf},<br \/>\r\ndoi = {10.1016\/j.compenvurbsys.2024.102111},<br \/>\r\nyear  = {2024},<br \/>\r\ndate = {2024-04-06},<br \/>\r\njournal = {Computers, Environment and Urban Systems},<br \/>\r\nvolume = {110},<br \/>\r\npages = {102111},<br \/>\r\nabstract = {The onset of the global Covid-19 pandemic in early 2020 brought many transportation systems in North America to a standstill. As life returned to normal, various modes of transportation exhibited differing rates of recovery, with disparities across regions. Limited research has delved into the regional variations in the recovery of these modes of transit over the past years. Such analysis is crucial for gaining insights into urban recovery and resilience, as well as understanding the factors influencing such recovery. In this work, we investigate the usage recovery of taxis, ride-hailing services, and subway ridership following the Covid-19 pandemic. We focus on New York City as our case study, employing clustering techniques to identify neighborhoods with similar recovery patterns. Furthermore, we examine the socio-economic, demographic, and built-environment factors contributing to regional variations in this recovery. Our research findings reveal that different modes of transportation responded differently to the pandemic, and these responses exhibited regional disparities. These findings hold significance for future health-related emergency response strategies and the regulation of existing transportation infrastructure.<br \/>\r\n},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('63','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_63\" style=\"display:none;\"><div class=\"tp_abstract_entry\">The onset of the global Covid-19 pandemic in early 2020 brought many transportation systems in North America to a standstill. As life returned to normal, various modes of transportation exhibited differing rates of recovery, with disparities across regions. Limited research has delved into the regional variations in the recovery of these modes of transit over the past years. Such analysis is crucial for gaining insights into urban recovery and resilience, as well as understanding the factors influencing such recovery. In this work, we investigate the usage recovery of taxis, ride-hailing services, and subway ridership following the Covid-19 pandemic. We focus on New York City as our case study, employing clustering techniques to identify neighborhoods with similar recovery patterns. Furthermore, we examine the socio-economic, demographic, and built-environment factors contributing to regional variations in this recovery. Our research findings reveal that different modes of transportation responded differently to the pandemic, and these responses exhibited regional disparities. These findings hold significance for future health-related emergency response strategies and the regulation of existing transportation infrastructure.<br \/>\r\n<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('63','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_63\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-file-pdf\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/grantmckenzie.com\/academics\/Qiang_2024.pdf\" title=\"https:\/\/grantmckenzie.com\/academics\/Qiang_2024.pdf\" target=\"_blank\">https:\/\/grantmckenzie.com\/academics\/Qiang_2024.pdf<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1016\/j.compenvurbsys.2024.102111\" title=\"Follow DOI:10.1016\/j.compenvurbsys.2024.102111\" target=\"_blank\">doi:10.1016\/j.compenvurbsys.2024.102111<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('63','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> Verma, Priyanka;  McKenzie, Grant<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('62','tp_links')\" style=\"cursor:pointer;\">Regional Comparison of Socio-Demographic Variation in Urban E-scooter Usage<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">Environment and Planning B: Urban Analytics and City Science, <\/span><span class=\"tp_pub_additional_year\">2024<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_62\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('62','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_62\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('62','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_62\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('62','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_62\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{Verma2024,<br \/>\r\ntitle = {Regional Comparison of Socio-Demographic Variation in Urban E-scooter Usage},<br \/>\r\nauthor = {Priyanka Verma and Grant McKenzie},<br \/>\r\nurl = {https:\/\/grantmckenzie.com\/academics\/Verma_2024.pdf},<br \/>\r\nyear  = {2024},<br \/>\r\ndate = {2024-03-26},<br \/>\r\nurldate = {2024-03-09},<br \/>\r\njournal = {Environment and Planning B: Urban Analytics and City Science},<br \/>\r\nabstract = {In recent years we have witnessed explosive growth in the shared, free-floating, electric scooter industry. While still controversial in many North American cities, a number of large e-scooter operators have managed to carve out a piece of the urban transportation landscape. As these vehicles shift from novelty services to increasingly reliable modes of short personal travel, the discussion has turned to investigating who exactly benefits from these micromobility services and who are being left behind. Though population surveys have been administered to identify the socio-demographic characteristics of e-scooter riders in the past, little work has linked these characteristics through trips, or investigated the regional variation in these demographic factors. In this work we explore the variability and similarities in e-scooter rider characteristics across three major U.S. cities. To accomplish this, we apply a Moran\u2019s Eigenvector Spatial Filtering linear regression model and compare our results to more commonly used spatial regression approaches. Our results indicate that the spatial filtering approach outperforms other methods in identifying socio-demographic characteristics of e-scooter users, across multiple regions. We find that many socio-demographics associated with e-scooter usage are regionally variant, despite younger users making up the core user base in all cities. There are variations in usage based on gender, income, and race across cities with Black and Hispanic populations remaining underserved. The implications of these findings are discussed.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('62','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_62\" style=\"display:none;\"><div class=\"tp_abstract_entry\">In recent years we have witnessed explosive growth in the shared, free-floating, electric scooter industry. While still controversial in many North American cities, a number of large e-scooter operators have managed to carve out a piece of the urban transportation landscape. As these vehicles shift from novelty services to increasingly reliable modes of short personal travel, the discussion has turned to investigating who exactly benefits from these micromobility services and who are being left behind. Though population surveys have been administered to identify the socio-demographic characteristics of e-scooter riders in the past, little work has linked these characteristics through trips, or investigated the regional variation in these demographic factors. In this work we explore the variability and similarities in e-scooter rider characteristics across three major U.S. cities. To accomplish this, we apply a Moran\u2019s Eigenvector Spatial Filtering linear regression model and compare our results to more commonly used spatial regression approaches. Our results indicate that the spatial filtering approach outperforms other methods in identifying socio-demographic characteristics of e-scooter users, across multiple regions. We find that many socio-demographics associated with e-scooter usage are regionally variant, despite younger users making up the core user base in all cities. There are variations in usage based on gender, income, and race across cities with Black and Hispanic populations remaining underserved. The implications of these findings are discussed.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('62','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_62\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-file-pdf\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/grantmckenzie.com\/academics\/Verma_2024.pdf\" title=\"https:\/\/grantmckenzie.com\/academics\/Verma_2024.pdf\" target=\"_blank\">https:\/\/grantmckenzie.com\/academics\/Verma_2024.pdf<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('62','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><h3 class=\"tp_h3\" id=\"tp_h3_2023\">2023<\/h3><div class=\"tp_publication tp_publication_inbook\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> McKenzie, Grant;  Zhang, Hongyu;  Gambs, Sebastien<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('61','tp_links')\" style=\"cursor:pointer;\">Privacy and Ethics in GeoAI<\/a> <span class=\"tp_pub_type tp_  inbook\">Book Chapter<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span> Gao, Song;  Hu, Yingjie;  Li, Wenwen (Ed.): <span class=\"tp_pub_additional_booktitle\">Handbook of Geospatial Artificial Intelligence, <\/span><span class=\"tp_pub_additional_chapter\"> Chapter 19, <\/span><span class=\"tp_pub_additional_publisher\">CRC Press, <\/span><span class=\"tp_pub_additional_edition\">1, <\/span><span class=\"tp_pub_additional_year\">2023<\/span>, <span class=\"tp_pub_additional_isbn\">ISBN: 9781003308423<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_61\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('61','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_61\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('61','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_61\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('61','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_61\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@inbook{McKenzie2023c,<br \/>\r\ntitle = {Privacy and Ethics in GeoAI},<br \/>\r\nauthor = {Grant McKenzie and Hongyu Zhang and Sebastien Gambs},<br \/>\r\neditor = {Song Gao and Yingjie Hu and Wenwen Li},<br \/>\r\nurl = {https:\/\/grantmckenzie.com\/academics\/Privacy_GeoAI.pdf},<br \/>\r\ndoi = {https:\/\/doi.org\/10.1201\/9781003308423},<br \/>\r\nisbn = {9781003308423},<br \/>\r\nyear  = {2023},<br \/>\r\ndate = {2023-12-28},<br \/>\r\nurldate = {2023-12-28},<br \/>\r\nbooktitle = {Handbook of Geospatial Artificial Intelligence},<br \/>\r\npublisher = {CRC Press},<br \/>\r\nedition = {1},<br \/>\r\nchapter = {19},<br \/>\r\nabstract = {Any advancement in technology is accompanied by new concerns over its ethical use and impacts on privacy. While a notoriously difficult term to define, privacy as it relates to technology usage, can be described as the ability of an individual or group to control their personal information. Like many ethical concepts, this definition evolves with changes in societal and technical norms. The emergence of machine learning and related artificial intelligence techniques has again shifted societal concerns about the privacy of our persons, socio-demographic group membership, and personal data. Location data are particularly sensitive as they link information across sources and can be used to infer a wide variety of personal information. This makes data privacy one of the most important ethical discussions within the field of geographic artificial intelligence (GeoAI). The main objective of this chapter is to explore the unique privacy concerns associated with AI techniques used for analyzing geospatial information. After providing an overview of the topic, we describe some of the most common techniques and leading application areas through which data privacy and GeoAI are converging. Finally, we suggest a number of ways that privacy within GeoAI can improve and highlight emerging topics within the field.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {inbook}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('61','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_61\" style=\"display:none;\"><div class=\"tp_abstract_entry\">Any advancement in technology is accompanied by new concerns over its ethical use and impacts on privacy. While a notoriously difficult term to define, privacy as it relates to technology usage, can be described as the ability of an individual or group to control their personal information. Like many ethical concepts, this definition evolves with changes in societal and technical norms. The emergence of machine learning and related artificial intelligence techniques has again shifted societal concerns about the privacy of our persons, socio-demographic group membership, and personal data. Location data are particularly sensitive as they link information across sources and can be used to infer a wide variety of personal information. This makes data privacy one of the most important ethical discussions within the field of geographic artificial intelligence (GeoAI). The main objective of this chapter is to explore the unique privacy concerns associated with AI techniques used for analyzing geospatial information. After providing an overview of the topic, we describe some of the most common techniques and leading application areas through which data privacy and GeoAI are converging. Finally, we suggest a number of ways that privacy within GeoAI can improve and highlight emerging topics within the field.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('61','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_61\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-file-pdf\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/grantmckenzie.com\/academics\/Privacy_GeoAI.pdf\" title=\"https:\/\/grantmckenzie.com\/academics\/Privacy_GeoAI.pdf\" target=\"_blank\">https:\/\/grantmckenzie.com\/academics\/Privacy_GeoAI.pdf<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/https:\/\/doi.org\/10.1201\/9781003308423\" title=\"Follow DOI:https:\/\/doi.org\/10.1201\/9781003308423\" target=\"_blank\">doi:https:\/\/doi.org\/10.1201\/9781003308423<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('61','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_inproceedings\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> Brunila, Mikael;  LaViolette, Jack;  CH-Wang, Sky;  Verma, Priyanka;  F\u00e9r\u00e9, Clara;  McKenzie, Grant<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('58','tp_links')\" style=\"cursor:pointer;\">Toward a Critical Toponymy Framework for Named Entity Recognition: A Case Study of Airbnb in New York City<\/a> <span class=\"tp_pub_label_award\" title=\"Best Paper\"><i class=\"fas fa-trophy\"><\/i> Best Paper<\/span> <span class=\"tp_pub_type tp_  inproceedings\">Proceedings Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_booktitle\">Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP2023), <\/span><span class=\"tp_pub_additional_year\">2023<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_58\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('58','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_58\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('58','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_58\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('58','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_58\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@inproceedings{Brunila2023,<br \/>\r\ntitle = {Toward a Critical Toponymy Framework for Named Entity Recognition: A Case Study of Airbnb in New York City},<br \/>\r\nauthor = {Mikael Brunila and Jack LaViolette and Sky CH-Wang and Priyanka Verma and Clara F\u00e9r\u00e9 and Grant McKenzie},<br \/>\r\ndoi = {https:\/\/doi.org\/10.48550\/arXiv.2310.15302},<br \/>\r\nyear  = {2023},<br \/>\r\ndate = {2023-12-10},<br \/>\r\nurldate = {2023-10-25},<br \/>\r\nbooktitle = {Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP2023)},<br \/>\r\nabstract = {Critical toponymy examines the dynamics of power, capital, and resistance through place names and the sites to which they refer. Studies here have traditionally focused on the semantic content of toponyms and the top-down institutional processes that produce them. However, they have generally ignored the ways in which toponyms are used by ordinary people in everyday discourse, as well as the other strategies of geospatial description that accompany and contextualize toponymic reference. Here, we develop computational methods to measure how cultural and economic capital shape the ways in which people refer to places, through a novel annotated dataset of 47,440 New York City Airbnb listings from the 2010s. Building on this dataset, we introduce a new named entity recognition (NER) model able to identify important discourse categories integral to the characterization of place. Our findings point toward new directions for critical toponymy and to a range of previously understudied linguistic signals relevant to research on neighborhood status, housing and tourism markets, and gentrification.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {inproceedings}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('58','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_58\" style=\"display:none;\"><div class=\"tp_abstract_entry\">Critical toponymy examines the dynamics of power, capital, and resistance through place names and the sites to which they refer. Studies here have traditionally focused on the semantic content of toponyms and the top-down institutional processes that produce them. However, they have generally ignored the ways in which toponyms are used by ordinary people in everyday discourse, as well as the other strategies of geospatial description that accompany and contextualize toponymic reference. Here, we develop computational methods to measure how cultural and economic capital shape the ways in which people refer to places, through a novel annotated dataset of 47,440 New York City Airbnb listings from the 2010s. Building on this dataset, we introduce a new named entity recognition (NER) model able to identify important discourse categories integral to the characterization of place. Our findings point toward new directions for critical toponymy and to a range of previously understudied linguistic signals relevant to research on neighborhood status, housing and tourism markets, and gentrification.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('58','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_58\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/https:\/\/doi.org\/10.48550\/arXiv.2310.15302\" title=\"Follow DOI:https:\/\/doi.org\/10.48550\/arXiv.2310.15302\" target=\"_blank\">doi:https:\/\/doi.org\/10.48550\/arXiv.2310.15302<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('58','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_inproceedings\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> Qiang, Dan;  McKenzie, Grant<\/p><p class=\"tp_pub_title\">Mobility Vitality: Assessing Neighborhood Similarity Through Transportation Patterns In New York City <span class=\"tp_pub_type tp_  inproceedings\">Proceedings Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_booktitle\">Proceedings of the 12th International Conference on Geographic Information Science, <\/span><span class=\"tp_pub_additional_publisher\">Schloss Dagstuhl -- Leibniz-Zentrum fur Informatik, <\/span><span class=\"tp_pub_additional_year\">2023<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_59\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('59','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_59\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('59','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_59\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@inproceedings{Qiang2023,<br \/>\r\ntitle = {Mobility Vitality: Assessing Neighborhood Similarity Through Transportation Patterns In New York City},<br \/>\r\nauthor = {Dan Qiang and Grant McKenzie},<br \/>\r\nyear  = {2023},<br \/>\r\ndate = {2023-08-31},<br \/>\r\nbooktitle = {Proceedings of the 12th International Conference on Geographic Information Science},<br \/>\r\nvolume = {277},<br \/>\r\npublisher = {Schloss Dagstuhl -- Leibniz-Zentrum fur Informatik},<br \/>\r\nseries = {Leibniz International Proceedings in Informatics (LIPIcs)},<br \/>\r\nabstract = {Though numerous studies have examined human mobility within an urban environment, few have explored the concept of urban vitality purely through the lens of urban transportation. Given the importance of different modes of transportation within a city, such analysis is necessary. In this short paper, we introduce the novel concept of mobility vitality by integrating human mobility and urban vitality, offering a multilayered framework to assess the degree of transportation and mobility within and between regions. The mobility patterns of three transportation modes, namely subway, taxicab, and bike-share, are first examined independently. These patterns are then aggregated to form the composite measure of static mobility vitality. Through this measure, we evaluate similarities between neighborhoods. Our results observed significant spatial differences in the travel patterns of three transportation modes on weekdays and weekends. Moreover, neighborhoods with high static mobility vitality have relatively similar mobility patterns. Ultimately, this approach aims to find neighborhoods with imbalanced transportation infrastructure or inadequate public.<br \/>\r\n},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {inproceedings}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('59','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_59\" style=\"display:none;\"><div class=\"tp_abstract_entry\">Though numerous studies have examined human mobility within an urban environment, few have explored the concept of urban vitality purely through the lens of urban transportation. Given the importance of different modes of transportation within a city, such analysis is necessary. In this short paper, we introduce the novel concept of mobility vitality by integrating human mobility and urban vitality, offering a multilayered framework to assess the degree of transportation and mobility within and between regions. The mobility patterns of three transportation modes, namely subway, taxicab, and bike-share, are first examined independently. These patterns are then aggregated to form the composite measure of static mobility vitality. Through this measure, we evaluate similarities between neighborhoods. Our results observed significant spatial differences in the travel patterns of three transportation modes on weekdays and weekends. Moreover, neighborhoods with high static mobility vitality have relatively similar mobility patterns. Ultimately, this approach aims to find neighborhoods with imbalanced transportation infrastructure or inadequate public.<br \/>\r\n<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('59','tp_abstract')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_inproceedings\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> Brunila, Mikael;  Verma, Priyanka;  McKenzie, Grant<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('60','tp_links')\" style=\"cursor:pointer;\">When Everything Is &quot;Nearby&quot;: How Airbnb Listings in New York City Exaggerate Proximity<\/a> <span class=\"tp_pub_type tp_  inproceedings\">Proceedings Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_booktitle\">Proceedings of the 12th International Conference on Geographic Information Science, <\/span><span class=\"tp_pub_additional_publisher\">Schloss Dagstuhl -- Leibniz-Zentrum fur Informatik, <\/span><span class=\"tp_pub_additional_year\">2023<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_60\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('60','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_60\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('60','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_60\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('60','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_60\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@inproceedings{Brunila2023b,<br \/>\r\ntitle = {When Everything Is \"Nearby\": How Airbnb Listings in New York City Exaggerate Proximity},<br \/>\r\nauthor = {Mikael Brunila and Priyanka Verma and Grant McKenzie},<br \/>\r\nurl = {https:\/\/drops.dagstuhl.de\/opus\/volltexte\/2023\/18911\/},<br \/>\r\ndoi = {10.4230\/LIPIcs.GIScience.2023.16},<br \/>\r\nyear  = {2023},<br \/>\r\ndate = {2023-08-31},<br \/>\r\nbooktitle = {Proceedings of the 12th International Conference on Geographic Information Science},<br \/>\r\nvolume = {277},<br \/>\r\npublisher = {Schloss Dagstuhl -- Leibniz-Zentrum fur Informatik},<br \/>\r\nseries = {Leibniz International Proceedings in Informatics (LIPIcs)},<br \/>\r\nabstract = {In recent years, the emergence and rapid growth of short-term rental (STR) markets has exerted considerable influence on real estate in most large cities across the world. Central location and transit access are two primary factors associated with the prevalence and expansion of STRs, including Airbnbs. Nevertheless, perhaps due to methodological challenges, no research has addressed how location and proximity are represented in the titles and descriptions of STRs. In this paper, we introduce a new methodological pipeline to extract spatial relations from text and show that expressions of distance in STR listings can indeed be quantified and measured against real-world distances. We then comparatively analyze Airbnb reviews (written by guests) and listings (written by hosts) from New York City in order to demonstrate systematically how listings exaggerate proximity compared to reviews. Moreover, we discover spatial patterns to these differences that warrant further investigation.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {inproceedings}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('60','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_60\" style=\"display:none;\"><div class=\"tp_abstract_entry\">In recent years, the emergence and rapid growth of short-term rental (STR) markets has exerted considerable influence on real estate in most large cities across the world. Central location and transit access are two primary factors associated with the prevalence and expansion of STRs, including Airbnbs. Nevertheless, perhaps due to methodological challenges, no research has addressed how location and proximity are represented in the titles and descriptions of STRs. In this paper, we introduce a new methodological pipeline to extract spatial relations from text and show that expressions of distance in STR listings can indeed be quantified and measured against real-world distances. We then comparatively analyze Airbnb reviews (written by guests) and listings (written by hosts) from New York City in order to demonstrate systematically how listings exaggerate proximity compared to reviews. Moreover, we discover spatial patterns to these differences that warrant further investigation.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('60','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_60\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-globe\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/drops.dagstuhl.de\/opus\/volltexte\/2023\/18911\/\" title=\"https:\/\/drops.dagstuhl.de\/opus\/volltexte\/2023\/18911\/\" target=\"_blank\">https:\/\/drops.dagstuhl.de\/opus\/volltexte\/2023\/18911\/<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.4230\/LIPIcs.GIScience.2023.16\" title=\"Follow DOI:10.4230\/LIPIcs.GIScience.2023.16\" target=\"_blank\">doi:10.4230\/LIPIcs.GIScience.2023.16<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('60','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_inproceedings\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> McKenzie, Grant;  Zhang, Hongyu<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('57','tp_links')\" style=\"cursor:pointer;\">Platial k-anonymity: Improving location anonymity through temporal popularity signatures<\/a> <span class=\"tp_pub_label_award\" title=\"Best Paper\"><i class=\"fas fa-trophy\"><\/i> Best Paper<\/span> <span class=\"tp_pub_type tp_  inproceedings\">Proceedings Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_booktitle\">Proceedings of the 12th International Conference on Geographic Information Science, <\/span><span class=\"tp_pub_additional_publisher\">Schloss Dagstuhl -- Leibniz-Zentrum fur Informatik, <\/span><span class=\"tp_pub_additional_year\">2023<\/span>, <span class=\"tp_pub_additional_issn\">ISSN: 1868-8969<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_57\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('57','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_57\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('57','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_57\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('57','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_57\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@inproceedings{McKenzie2023b,<br \/>\r\ntitle = {Platial k-anonymity: Improving location anonymity through temporal popularity signatures},<br \/>\r\nauthor = {Grant McKenzie and Hongyu Zhang },<br \/>\r\nurl = {https:\/\/drops.dagstuhl.de\/opus\/volltexte\/2023\/18904\/},<br \/>\r\nissn = {1868-8969},<br \/>\r\nyear  = {2023},<br \/>\r\ndate = {2023-08-31},<br \/>\r\nurldate = {2023-08-31},<br \/>\r\nbooktitle = {Proceedings of the 12th International Conference on Geographic Information Science},<br \/>\r\nvolume = {277},<br \/>\r\npublisher = {Schloss Dagstuhl -- Leibniz-Zentrum fur Informatik},<br \/>\r\nseries = {Leibniz International Proceedings in Informatics (LIPIcs)},<br \/>\r\nabstract = {While it is increasingly necessary in today's digital society, sharing personal location information comes at a cost.  Sharing one's precise place of interest, e.g., Compass Coffee, enables a range of location-based services, but substantially reduces the individual's privacy.  Methods have been developed to obfuscate and anonymize location data while still maintaining a degree of utility.  One such approach, spatial k-anonymity, aims to ensure an individual's level of anonymity by reporting their location as a set of k potential locations rather than their actual location alone.  Larger values of k increase spatial anonymity while decreasing the utility of the location information.  Typical examples of spatial k-anonymized datasets present elements as simple geographic points with no attributes or contextual information.  In this work, we demonstrate that the addition of publicly available contextual data can significantly reduce the anonymity of a k-anonymized dataset.  Through the analysis of place type temporal visitation patterns, hours of operation, and popularity values, one's anonymity can decreased by more than 50 percent.  We propose a platial k-anonymity approach that leverages a combination of temporal popularity signatures and report the amount that k must increase in order to maintain a certain level of anonymity. Finally, a method for reporting platial k-anonymous regions is presented and the implications of our methods are discussed.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {inproceedings}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('57','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_57\" style=\"display:none;\"><div class=\"tp_abstract_entry\">While it is increasingly necessary in today's digital society, sharing personal location information comes at a cost.  Sharing one's precise place of interest, e.g., Compass Coffee, enables a range of location-based services, but substantially reduces the individual's privacy.  Methods have been developed to obfuscate and anonymize location data while still maintaining a degree of utility.  One such approach, spatial k-anonymity, aims to ensure an individual's level of anonymity by reporting their location as a set of k potential locations rather than their actual location alone.  Larger values of k increase spatial anonymity while decreasing the utility of the location information.  Typical examples of spatial k-anonymized datasets present elements as simple geographic points with no attributes or contextual information.  In this work, we demonstrate that the addition of publicly available contextual data can significantly reduce the anonymity of a k-anonymized dataset.  Through the analysis of place type temporal visitation patterns, hours of operation, and popularity values, one's anonymity can decreased by more than 50 percent.  We propose a platial k-anonymity approach that leverages a combination of temporal popularity signatures and report the amount that k must increase in order to maintain a certain level of anonymity. Finally, a method for reporting platial k-anonymous regions is presented and the implications of our methods are discussed.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('57','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_57\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-globe\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/drops.dagstuhl.de\/opus\/volltexte\/2023\/18904\/\" title=\"https:\/\/drops.dagstuhl.de\/opus\/volltexte\/2023\/18904\/\" target=\"_blank\">https:\/\/drops.dagstuhl.de\/opus\/volltexte\/2023\/18904\/<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('57','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> McKenzie, Grant;  Battersby, Sarah;  Setlur, Vidya<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('56','tp_links')\" style=\"cursor:pointer;\">MixMap: A user-driven approach to place-based semantic similarity<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">Cartography and Geographic Information Science, <\/span><span class=\"tp_pub_additional_pages\">pp. 1-16, <\/span><span class=\"tp_pub_additional_year\">2023<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_56\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('56','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_56\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('56','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_56\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('56','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_56\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{McKenzie2023,<br \/>\r\ntitle = {MixMap: A user-driven approach to place-based semantic similarity},<br \/>\r\nauthor = {Grant McKenzie and Sarah Battersby and Vidya Setlur},<br \/>\r\ndoi = {10.1080\/15230406.2023.2176930},<br \/>\r\nyear  = {2023},<br \/>\r\ndate = {2023-03-02},<br \/>\r\nurldate = {2023-03-02},<br \/>\r\njournal = {Cartography and Geographic Information Science},<br \/>\r\npages = {1-16},<br \/>\r\npublisher = {Taylor & Francis},<br \/>\r\nabstract = {What other locations are like my neighborhood? How? Why? The heart of many spatial analyses is in finding similarities or dissimilarities between locations. Discovering patterns and interpreting similarity is a complicated process that is based on both the spatial characteristics and the semantics or meaning that we assign to place. Human conceptualization of similarity in locations is multi-faceted and cannot be captured with a simple assessment of single numeric attributes like population density or median income; however, these quantifiable attributes are the basis for an initial pass of sense-making. MixMap facilitates the incorporation of similarity measures and spatial analytics to provide an information reduction (or semantic generalization) that brings the user closer to actionable insights. Through a preliminary evaluation of MixMap, we found that the tool supports the geospatial inquiry of determining similarity between regions, where participants can manipulate individual weights of the various attributes describing these locations. Based on feedback and observations from the study, we discuss potential implications and considerations for exploring the role of context and additional place-specific parameters for computing similarity, as well as understanding the nuances of semantics for place similarity in geospatial analysis tools.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('56','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_56\" style=\"display:none;\"><div class=\"tp_abstract_entry\">What other locations are like my neighborhood? How? Why? The heart of many spatial analyses is in finding similarities or dissimilarities between locations. Discovering patterns and interpreting similarity is a complicated process that is based on both the spatial characteristics and the semantics or meaning that we assign to place. Human conceptualization of similarity in locations is multi-faceted and cannot be captured with a simple assessment of single numeric attributes like population density or median income; however, these quantifiable attributes are the basis for an initial pass of sense-making. MixMap facilitates the incorporation of similarity measures and spatial analytics to provide an information reduction (or semantic generalization) that brings the user closer to actionable insights. Through a preliminary evaluation of MixMap, we found that the tool supports the geospatial inquiry of determining similarity between regions, where participants can manipulate individual weights of the various attributes describing these locations. Based on feedback and observations from the study, we discuss potential implications and considerations for exploring the role of context and additional place-specific parameters for computing similarity, as well as understanding the nuances of semantics for place similarity in geospatial analysis tools.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('56','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_56\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1080\/15230406.2023.2176930\" title=\"Follow DOI:10.1080\/15230406.2023.2176930\" target=\"_blank\">doi:10.1080\/15230406.2023.2176930<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('56','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><h3 class=\"tp_h3\" id=\"tp_h3_2022\">2022<\/h3><div class=\"tp_publication tp_publication_inproceedings\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> Zhang, Hongyu;  McKenzie, Grant<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('54','tp_links')\" style=\"cursor:pointer;\">Towards place-based privacy: Challenges and opportunities in the \u201csmart\u201d world<\/a> <span class=\"tp_pub_type tp_  inproceedings\">Proceedings Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_booktitle\">IEEE International Symposium on Technology and Society 2022, <\/span><span class=\"tp_pub_additional_publisher\">IEEE, <\/span><span class=\"tp_pub_additional_year\">2022<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_54\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('54','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_54\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('54','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_54\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('54','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_54\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@inproceedings{Zhang2022b,<br \/>\r\ntitle = {Towards place-based privacy: Challenges and opportunities in the \u201csmart\u201d world},<br \/>\r\nauthor = {Hongyu Zhang and Grant McKenzie },<br \/>\r\nurl = {https:\/\/grantmckenzie.com\/academics\/HZhang_ISTAS_2022.pdf},<br \/>\r\nyear  = {2022},<br \/>\r\ndate = {2022-11-10},<br \/>\r\nurldate = {2022-11-10},<br \/>\r\nbooktitle = {IEEE International Symposium on Technology and Society 2022},<br \/>\r\npublisher = {IEEE},<br \/>\r\nabstract = {The emergence of \u201csmart\u201d technologies has given rise to new interaction models merging our physical realities with our digital environments. As a result, new privacy threats have emerged, substantially impacting both individuals and groups. In this short paper, we summarize many of the privacy challenges we face in the smart and connected world, and identify opportunities for further research. Drawing from the recent literature on geoprivacy, user-tailored privacy, and group privacy, we explore this topic through the lens of contextually aware, place-based, or platial, information analysis.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {inproceedings}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('54','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_54\" style=\"display:none;\"><div class=\"tp_abstract_entry\">The emergence of \u201csmart\u201d technologies has given rise to new interaction models merging our physical realities with our digital environments. As a result, new privacy threats have emerged, substantially impacting both individuals and groups. In this short paper, we summarize many of the privacy challenges we face in the smart and connected world, and identify opportunities for further research. Drawing from the recent literature on geoprivacy, user-tailored privacy, and group privacy, we explore this topic through the lens of contextually aware, place-based, or platial, information analysis.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('54','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_54\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-file-pdf\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/grantmckenzie.com\/academics\/HZhang_ISTAS_2022.pdf\" title=\"https:\/\/grantmckenzie.com\/academics\/HZhang_ISTAS_2022.pdf\" target=\"_blank\">https:\/\/grantmckenzie.com\/academics\/HZhang_ISTAS_2022.pdf<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('54','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_inproceedings\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> Brunila, Mikael;  McConnell, Michael;  Grigg, Stalgia<\/p><p class=\"tp_pub_title\">DRIFT: End-to-end encrypted spatial feature sharing &amp; instant messaging <span class=\"tp_pub_type tp_  inproceedings\">Proceedings Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_booktitle\">Proceedings of the 6th ACM SIGSPATIAL Workshop on Location-based Recommendations, Geosocial Networks and Geoadvertising, <\/span><span class=\"tp_pub_additional_publisher\">ACM, <\/span><span class=\"tp_pub_additional_year\">2022<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_55\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('55','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_55\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('55','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_55\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@inproceedings{Brunila2022b,<br \/>\r\ntitle = {DRIFT: End-to-end encrypted spatial feature sharing & instant messaging},<br \/>\r\nauthor = {Mikael Brunila and Michael McConnell and Stalgia Grigg},<br \/>\r\nyear  = {2022},<br \/>\r\ndate = {2022-11-01},<br \/>\r\nbooktitle = {Proceedings of the 6th ACM SIGSPATIAL Workshop on Location-based Recommendations, Geosocial Networks and Geoadvertising},<br \/>\r\npublisher = {ACM},<br \/>\r\nabstract = {Most online communication today is inherently temporal and aspatial. Instant messaging services are structured around a timeline inter- face which prioritizes a linear succession of events and guides our attention towards the novel. In this way, the different textures of so- cial life are lost in linear reduction. In this paper, we present DRIFT, a novel and open-source instant messaging application framework, based on a different paradigm of communication that preserves temporality but organizes it around space. Instead of the timeline, our application grounds messaging in the map and its pins, offering users a tool that encourages spatio-temporal communication and the sharing of spatial features. Given increasing concerns about the safety and privacy of online user interaction, we integrate state-of- the art encryption as a core feature of our application. Firstly, to protect user messages and map pins, we implement end-to-end en- cryption with the Double Ratchet key management algorithm and the open standard Matrix protocol. Secondly, to maintain location privacy, we allow users to batch download map tilesets and machine learning models to perform operations such as search entirely on device, avoiding compromising API calls to cloud services. With these combined features, DRIFT aims to introduce a new model for online interaction that upends the short attention span imposed by the narrow timeline and replace it with a spatio-temporally rich and secure instant messaging tool for both laymen and more vulnerable users such as journalists, human rights activists, and whistleblowers.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {inproceedings}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('55','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_55\" style=\"display:none;\"><div class=\"tp_abstract_entry\">Most online communication today is inherently temporal and aspatial. Instant messaging services are structured around a timeline inter- face which prioritizes a linear succession of events and guides our attention towards the novel. In this way, the different textures of so- cial life are lost in linear reduction. In this paper, we present DRIFT, a novel and open-source instant messaging application framework, based on a different paradigm of communication that preserves temporality but organizes it around space. Instead of the timeline, our application grounds messaging in the map and its pins, offering users a tool that encourages spatio-temporal communication and the sharing of spatial features. Given increasing concerns about the safety and privacy of online user interaction, we integrate state-of- the art encryption as a core feature of our application. Firstly, to protect user messages and map pins, we implement end-to-end en- cryption with the Double Ratchet key management algorithm and the open standard Matrix protocol. Secondly, to maintain location privacy, we allow users to batch download map tilesets and machine learning models to perform operations such as search entirely on device, avoiding compromising API calls to cloud services. With these combined features, DRIFT aims to introduce a new model for online interaction that upends the short attention span imposed by the narrow timeline and replace it with a spatio-temporally rich and secure instant messaging tool for both laymen and more vulnerable users such as journalists, human rights activists, and whistleblowers.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('55','tp_abstract')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_inproceedings\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> Brunila, Mikael;  LaViolette, Jack<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('52','tp_links')\" style=\"cursor:pointer;\">What kind of company do words keep? Revisiting the distributional semantics of J.R. Firth &amp; Zellig Harris<\/a> <span class=\"tp_pub_type tp_  inproceedings\">Proceedings Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_booktitle\">Proceedings of the 2022 Annual Conference of the North American Chapter of the Association for Computational Linguistics, <\/span><span class=\"tp_pub_additional_year\">2022<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_52\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('52','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_52\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('52','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_52\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('52','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_52\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@inproceedings{Brunila2022,<br \/>\r\ntitle = {What kind of company do words keep? Revisiting the distributional semantics of J.R. Firth & Zellig Harris},<br \/>\r\nauthor = {Mikael Brunila and Jack LaViolette},<br \/>\r\nurl = {https:\/\/arxiv.org\/abs\/2205.07750},<br \/>\r\nyear  = {2022},<br \/>\r\ndate = {2022-07-10},<br \/>\r\nurldate = {2022-07-10},<br \/>\r\nbooktitle = {Proceedings of the 2022 Annual Conference of the North American Chapter of the Association for Computational Linguistics},<br \/>\r\nabstract = {The power of word embeddings is attributed to the linguistic theory that similar words will appear in similar contexts. This idea is specifically invoked by noting that \"you shall know a word by the company it keeps,\" a quote from British linguist J.R. Firth who, along with his American colleague Zellig Harris, is often credited with the invention of \"distributional semantics.\" While both Firth and Harris are cited in all major NLP textbooks and many foundational papers, the content and differences between their theories is seldom discussed. Engaging in a close reading of their work, we discover two distinct and in many ways divergent theories of meaning. One focuses exclusively on the internal workings of linguistic forms, while the other invites us to consider words in new company - not just with other linguistic elements, but also in a broader cultural and situational context. Contrasting these theories from the perspective of current debates in NLP, we discover in Firth a figure who could guide the field towards a more culturally grounded notion of semantics. We consider how an expanded notion of \"context\" might be modeled in practice through two different strategies: comparative stratification and syntagmatic extension.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {inproceedings}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('52','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_52\" style=\"display:none;\"><div class=\"tp_abstract_entry\">The power of word embeddings is attributed to the linguistic theory that similar words will appear in similar contexts. This idea is specifically invoked by noting that &quot;you shall know a word by the company it keeps,&quot; a quote from British linguist J.R. Firth who, along with his American colleague Zellig Harris, is often credited with the invention of &quot;distributional semantics.&quot; While both Firth and Harris are cited in all major NLP textbooks and many foundational papers, the content and differences between their theories is seldom discussed. Engaging in a close reading of their work, we discover two distinct and in many ways divergent theories of meaning. One focuses exclusively on the internal workings of linguistic forms, while the other invites us to consider words in new company - not just with other linguistic elements, but also in a broader cultural and situational context. Contrasting these theories from the perspective of current debates in NLP, we discover in Firth a figure who could guide the field towards a more culturally grounded notion of semantics. We consider how an expanded notion of &quot;context&quot; might be modeled in practice through two different strategies: comparative stratification and syntagmatic extension.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('52','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_52\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"ai ai-arxiv\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/arxiv.org\/abs\/2205.07750\" title=\"https:\/\/arxiv.org\/abs\/2205.07750\" target=\"_blank\">https:\/\/arxiv.org\/abs\/2205.07750<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('52','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> Romm, Daniel;  Verma, Priyanka;  Karpinski, Elizabeth;  Sanders, Tracy;  McKenzie, Grant<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('53','tp_links')\" style=\"cursor:pointer;\">Differences in First-Mile and Last-Mile Behaviour in Candidate Multi-Modal Boston Bike-share Micromobility Trips<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">Journal of Transport Geography, <\/span><span class=\"tp_pub_additional_volume\">vol. 102, <\/span><span class=\"tp_pub_additional_issue\">iss. June, <\/span><span class=\"tp_pub_additional_year\">2022<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_resource_link\"><a id=\"tp_links_sh_53\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('53','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_53\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('53','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_53\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{Romm2022,<br \/>\r\ntitle = {Differences in First-Mile and Last-Mile Behaviour in Candidate Multi-Modal Boston Bike-share Micromobility Trips},<br \/>\r\nauthor = {Daniel Romm and Priyanka Verma and Elizabeth Karpinski and Tracy Sanders and Grant McKenzie},<br \/>\r\nurl = {https:\/\/doi.org\/10.1016\/j.jtrangeo.2022.103370},<br \/>\r\nyear  = {2022},<br \/>\r\ndate = {2022-06-07},<br \/>\r\nurldate = {2022-06-07},<br \/>\r\njournal = {Journal of Transport Geography},<br \/>\r\nvolume = {102},<br \/>\r\nissue = {June},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('53','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_53\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-globe\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/doi.org\/10.1016\/j.jtrangeo.2022.103370\" title=\"https:\/\/doi.org\/10.1016\/j.jtrangeo.2022.103370\" target=\"_blank\">https:\/\/doi.org\/10.1016\/j.jtrangeo.2022.103370<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('53','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> McKenzie, Grant;  Romm, Daniel;  Zhang, Hongyu;  Brunila, Mikael<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('51','tp_links')\" style=\"cursor:pointer;\">PrivyTo: A privacy preserving location sharing platform<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">Transactions in GIS, <\/span><span class=\"tp_pub_additional_year\">2022<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_51\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('51','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_51\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('51','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_51\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('51','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_51\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{McKenzie2022,<br \/>\r\ntitle = {PrivyTo: A privacy preserving location sharing platform},<br \/>\r\nauthor = {Grant McKenzie and Daniel Romm and Hongyu Zhang and Mikael Brunila},<br \/>\r\nurl = {https:\/\/grantmckenzie.com\/academics\/McKenzie2022_PrivyTo.pdf<br \/>\r\nhttps:\/\/onlinelibrary.wiley.com\/doi\/full\/10.1111\/tgis.12924},<br \/>\r\ndoi = {10.1111\/tgis.12924},<br \/>\r\nyear  = {2022},<br \/>\r\ndate = {2022-05-12},<br \/>\r\nurldate = {2022-03-11},<br \/>\r\njournal = {Transactions in GIS},<br \/>\r\npublisher = {Wiley Press},<br \/>\r\nabstract = {Concern over the privacy of one's personal location is at an all-time high, yet the desire to share our lives with friends, family, and the public persists. Current methods and applications for sharing location content with the range of people in our lives are sorely lacking.  Application users are often limited to sharing a single spatial resolution with all individuals, regardless of relation, and with little control over how this content is shared.  Processes for sharing typically involve allowing a for-profit company access to your location before it can be transmitted to the intended recipient.  In this work we propose a set of design goals and a design pattern for sharing personal location information that are realized through a prototype mobile web application.  Our approach is built on the novel idea of obfuscated and encrypted location views, and promotes a uniquely open method for sharing.  The intention of this paper is to demonstrate that location sharing need not require one to expose private location information to third parties, and that methods exist to put an individual back in control of their content.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('51','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_51\" style=\"display:none;\"><div class=\"tp_abstract_entry\">Concern over the privacy of one's personal location is at an all-time high, yet the desire to share our lives with friends, family, and the public persists. Current methods and applications for sharing location content with the range of people in our lives are sorely lacking.  Application users are often limited to sharing a single spatial resolution with all individuals, regardless of relation, and with little control over how this content is shared.  Processes for sharing typically involve allowing a for-profit company access to your location before it can be transmitted to the intended recipient.  In this work we propose a set of design goals and a design pattern for sharing personal location information that are realized through a prototype mobile web application.  Our approach is built on the novel idea of obfuscated and encrypted location views, and promotes a uniquely open method for sharing.  The intention of this paper is to demonstrate that location sharing need not require one to expose private location information to third parties, and that methods exist to put an individual back in control of their content.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('51','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_51\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-file-pdf\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/grantmckenzie.com\/academics\/McKenzie2022_PrivyTo.pdf\" title=\"https:\/\/grantmckenzie.com\/academics\/McKenzie2022_PrivyTo.pdf\" target=\"_blank\">https:\/\/grantmckenzie.com\/academics\/McKenzie2022_PrivyTo.pdf<\/a><\/li><li><i class=\"fas fa-globe\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/onlinelibrary.wiley.com\/doi\/full\/10.1111\/tgis.12924\" title=\"https:\/\/onlinelibrary.wiley.com\/doi\/full\/10.1111\/tgis.12924\" target=\"_blank\">https:\/\/onlinelibrary.wiley.com\/doi\/full\/10.1111\/tgis.12924<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1111\/tgis.12924\" title=\"Follow DOI:10.1111\/tgis.12924\" target=\"_blank\">doi:10.1111\/tgis.12924<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('51','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> Zhang, Hongyu;  McKenzie, Grant<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('50','tp_links')\" style=\"cursor:pointer;\">Rehumanize geoprivacy: From disclosure control to human perception<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">GeoJournal, <\/span><span class=\"tp_pub_additional_year\">2022<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_50\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('50','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_50\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('50','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_50\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('50','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_50\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{Zhang2022,<br \/>\r\ntitle = {Rehumanize geoprivacy: From disclosure control to human perception},<br \/>\r\nauthor = {Hongyu Zhang and Grant McKenzie},<br \/>\r\ndoi = {https:\/\/doi.org\/10.1007\/s10708-022-10598-4},<br \/>\r\nyear  = {2022},<br \/>\r\ndate = {2022-02-16},<br \/>\r\nurldate = {2022-01-31},<br \/>\r\njournal = {GeoJournal},<br \/>\r\npublisher = {Springer},<br \/>\r\nabstract = {Traditional boundaries between people are vanishing due to the rise of Internet of Things technology. Our smart devices keep us connected to the world, but also monitor our daily lives through an unprecedented amount data collection. As a result, defining privacy has become more complicated. Individuals want to leverage new technology (e.g., making friends through sharing private experiences) and also avoid unwanted consequences (e.g., targeted advertising).  In the age of ubiquitous digital content, geoprivacy is unique because concerns in this area are constantly changing and context-dependent. Multiple factors influence people\u2019s location disclosure decisions, including time, culture, demographics, spatial granularity, and trust. Existing research primarily focuses on the computational efforts of protecting  geoprivacy, while the variation of geoprivacy perceptions has yet to receive adequate attention in the data science literature. In this work, we explore geoprivacy from a cognate-based perspective and tackle our changing perception of the concept from multiple angles. Our objectives are to rehumanize this field from contextual, cultural, and economic dimensions and highlight the uniqueness of geodata under the broad topic of privacy. It is essential that we understand the spatial variations of geoprivacy perceptions in the era of big data. Masking geographic coordinates can no longer fully anonymize spatial data, and targeted geoprivacy protection needs to be further investigated to improve user experience.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('50','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_50\" style=\"display:none;\"><div class=\"tp_abstract_entry\">Traditional boundaries between people are vanishing due to the rise of Internet of Things technology. Our smart devices keep us connected to the world, but also monitor our daily lives through an unprecedented amount data collection. As a result, defining privacy has become more complicated. Individuals want to leverage new technology (e.g., making friends through sharing private experiences) and also avoid unwanted consequences (e.g., targeted advertising).  In the age of ubiquitous digital content, geoprivacy is unique because concerns in this area are constantly changing and context-dependent. Multiple factors influence people\u2019s location disclosure decisions, including time, culture, demographics, spatial granularity, and trust. Existing research primarily focuses on the computational efforts of protecting  geoprivacy, while the variation of geoprivacy perceptions has yet to receive adequate attention in the data science literature. In this work, we explore geoprivacy from a cognate-based perspective and tackle our changing perception of the concept from multiple angles. Our objectives are to rehumanize this field from contextual, cultural, and economic dimensions and highlight the uniqueness of geodata under the broad topic of privacy. It is essential that we understand the spatial variations of geoprivacy perceptions in the era of big data. Masking geographic coordinates can no longer fully anonymize spatial data, and targeted geoprivacy protection needs to be further investigated to improve user experience.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('50','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_50\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/https:\/\/doi.org\/10.1007\/s10708-022-10598-4\" title=\"Follow DOI:https:\/\/doi.org\/10.1007\/s10708-022-10598-4\" target=\"_blank\">doi:https:\/\/doi.org\/10.1007\/s10708-022-10598-4<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('50','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><h3 class=\"tp_h3\" id=\"tp_h3_2021\">2021<\/h3><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> McKenzie, Grant;  Mwenda, Kevin<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('46','tp_links')\" style=\"cursor:pointer;\">Identifying regional variation in place visit behavior during a global pandemic<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">Journal of Spatial Information Science, <\/span><span class=\"tp_pub_additional_volume\">vol. 2021, <\/span><span class=\"tp_pub_additional_number\">no. 23, <\/span><span class=\"tp_pub_additional_pages\">pp. 95-124, <\/span><span class=\"tp_pub_additional_year\">2021<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_46\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('46','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_46\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('46','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_46\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('46','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_46\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{McKenzie2021c,<br \/>\r\ntitle = {Identifying regional variation in place visit behavior during a global pandemic},<br \/>\r\nauthor = {Grant McKenzie and Kevin Mwenda},<br \/>\r\ndoi = {10.5311\/JOSIS.2021.23.170},<br \/>\r\nyear  = {2021},<br \/>\r\ndate = {2021-12-24},<br \/>\r\nurldate = {2021-11-11},<br \/>\r\njournal = {Journal of Spatial Information Science},<br \/>\r\nvolume = {2021},<br \/>\r\nnumber = {23},<br \/>\r\npages = {95-124},<br \/>\r\nabstract = {The emergence of the SARS-CoV-2 virus in 2019 lead to a global pandemic that altered the activity behavior of most people on our planet.  While government regulations and public concern modified visitation patterns to places of interest, little research has examined the nuanced changes in the length of time someone spends at a place, nor the regional variability of these changes. In this work, we examine place visit duration in four major U.S. cities, identify which place types saw the largest and smallest changes, and quantify variation between cities.  Furthermore, we identify socio-economic and demographic factors that contribute to changes in visit duration and demonstrate the varying influence of these factors by region.  The results of our analysis indicate that the pandemic's impact on visiting behavior varies between cities, though there are commonalities found in certain types of places.  Our findings suggest that places of interest within lower income communities experienced less change in visit duration than others.  An increase in the percentage of younger, Black or Hispanic populations within a community also resulted in a smaller decrease in visit duration than in other communities.   These findings offer insight into the factors that contribute to changes in visiting behavior and the resilience of communities to a global pandemic.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('46','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_46\" style=\"display:none;\"><div class=\"tp_abstract_entry\">The emergence of the SARS-CoV-2 virus in 2019 lead to a global pandemic that altered the activity behavior of most people on our planet.  While government regulations and public concern modified visitation patterns to places of interest, little research has examined the nuanced changes in the length of time someone spends at a place, nor the regional variability of these changes. In this work, we examine place visit duration in four major U.S. cities, identify which place types saw the largest and smallest changes, and quantify variation between cities.  Furthermore, we identify socio-economic and demographic factors that contribute to changes in visit duration and demonstrate the varying influence of these factors by region.  The results of our analysis indicate that the pandemic's impact on visiting behavior varies between cities, though there are commonalities found in certain types of places.  Our findings suggest that places of interest within lower income communities experienced less change in visit duration than others.  An increase in the percentage of younger, Black or Hispanic populations within a community also resulted in a smaller decrease in visit duration than in other communities.   These findings offer insight into the factors that contribute to changes in visiting behavior and the resilience of communities to a global pandemic.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('46','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_46\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.5311\/JOSIS.2021.23.170\" title=\"Follow DOI:10.5311\/JOSIS.2021.23.170\" target=\"_blank\">doi:10.5311\/JOSIS.2021.23.170<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('46','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_inproceedings\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> McKenzie, Grant<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('48','tp_links')\" style=\"cursor:pointer;\">Leveraging Place Reviews to Identify the Effects of COVID-19 on Canadian Tourism<\/a> <span class=\"tp_pub_type tp_  inproceedings\">Proceedings Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_booktitle\">Proceedings of the third International Symposium on Platial Information Science (PLATIAL'21), <\/span><span class=\"tp_pub_additional_address\">Enschede, the Netherlands, <\/span><span class=\"tp_pub_additional_year\">2021<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_48\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('48','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_48\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('48','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_48\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('48','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_48\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@inproceedings{McKenzie2021e,<br \/>\r\ntitle = {Leveraging Place Reviews to Identify the Effects of COVID-19 on Canadian Tourism},<br \/>\r\nauthor = {Grant McKenzie},<br \/>\r\nurl = {https:\/\/grantmckenzie.com\/academics\/McKenzie_Platial2021.pdf},<br \/>\r\ndoi = {10.5281\/zenodo.5767190},<br \/>\r\nyear  = {2021},<br \/>\r\ndate = {2021-12-08},<br \/>\r\nurldate = {2021-12-08},<br \/>\r\nbooktitle = {Proceedings of the third International Symposium on Platial Information Science (PLATIAL'21)},<br \/>\r\naddress = {Enschede, the Netherlands},<br \/>\r\nabstract = {The emergence of the COVID-19 pandemic disrupted travel world-wide and substantially impacted tourism in most countries. Though many governmental agencies and tourism boards have published data on the impact of the pandemic, in Canada, the vast majority of these data are reported at the national level or sparsely within individual regions. In this preliminary work, we leverage user-contributed tourist attraction reviews to better understand the nuanced changes in travel behavior resulting from the COVID-19 pandemic. We examine the regional impacts as well as the affects on different categories of tourism within Canada. The purpose of this short paper is to demonstrate the value of analyzing place-based user-generated tourism data and highlight some of the ways it can be leveraged by policy experts and tourism agencies.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {inproceedings}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('48','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_48\" style=\"display:none;\"><div class=\"tp_abstract_entry\">The emergence of the COVID-19 pandemic disrupted travel world-wide and substantially impacted tourism in most countries. Though many governmental agencies and tourism boards have published data on the impact of the pandemic, in Canada, the vast majority of these data are reported at the national level or sparsely within individual regions. In this preliminary work, we leverage user-contributed tourist attraction reviews to better understand the nuanced changes in travel behavior resulting from the COVID-19 pandemic. We examine the regional impacts as well as the affects on different categories of tourism within Canada. The purpose of this short paper is to demonstrate the value of analyzing place-based user-generated tourism data and highlight some of the ways it can be leveraged by policy experts and tourism agencies.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('48','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_48\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-file-pdf\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/grantmckenzie.com\/academics\/McKenzie_Platial2021.pdf\" title=\"https:\/\/grantmckenzie.com\/academics\/McKenzie_Platial2021.pdf\" target=\"_blank\">https:\/\/grantmckenzie.com\/academics\/McKenzie_Platial2021.pdf<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.5281\/zenodo.5767190\" title=\"Follow DOI:10.5281\/zenodo.5767190\" target=\"_blank\">doi:10.5281\/zenodo.5767190<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('48','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_inproceedings\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> Romm, Daniel;  Zhang, Hongyu;  Verma, Priyanka;  McKenzie, Grant;  Chen, Emily<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('49','tp_links')\" style=\"cursor:pointer;\">&quot;Data Horror&quot;: Mapping (Spatial) Data Privacy Violations onto a Cognitive Account of Horror<\/a> <span class=\"tp_pub_type tp_  inproceedings\">Proceedings Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_booktitle\">Proceedings of the Second Spatial Data Science Symposium , <\/span><span class=\"tp_pub_additional_year\">2021<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_49\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('49','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_49\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('49','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_49\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('49','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_49\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@inproceedings{Romm2021,<br \/>\r\ntitle = {\"Data Horror\": Mapping (Spatial) Data Privacy Violations onto a Cognitive Account of Horror},<br \/>\r\nauthor = {Daniel Romm and Hongyu Zhang and Priyanka Verma and Grant McKenzie and Emily Chen},<br \/>\r\nurl = {https:\/\/escholarship.org\/uc\/item\/7902g5hh},<br \/>\r\ndoi = {10.25436\/E23S3T},<br \/>\r\nyear  = {2021},<br \/>\r\ndate = {2021-12-01},<br \/>\r\nurldate = {2021-12-13},<br \/>\r\nbooktitle = {Proceedings of the Second Spatial Data Science Symposium },<br \/>\r\nseries = {Spatial Data Science Symposium 2021 Short Paper Proceedings},<br \/>\r\nabstract = {While spatial data privacy is not a new concern, recent information technology developments that allow for the increased collection and alternative use of spatial data have brought the discussion about geoprivacy back in focus. In this work, we draw a parallel between a conceptualization of horror based on work from cognitive scientists and philosophers, and the intrusiveness of current data collection methods, the unauthorized use of this data, and the transgressions made by data stewards. By drawing this connection, we discuss the familiar topic of data privacy through a novel lens that clarifies the importance of data privacy and elucidates the particular importance of geoprivacy.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {inproceedings}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('49','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_49\" style=\"display:none;\"><div class=\"tp_abstract_entry\">While spatial data privacy is not a new concern, recent information technology developments that allow for the increased collection and alternative use of spatial data have brought the discussion about geoprivacy back in focus. In this work, we draw a parallel between a conceptualization of horror based on work from cognitive scientists and philosophers, and the intrusiveness of current data collection methods, the unauthorized use of this data, and the transgressions made by data stewards. By drawing this connection, we discuss the familiar topic of data privacy through a novel lens that clarifies the importance of data privacy and elucidates the particular importance of geoprivacy.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('49','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_49\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-globe\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/escholarship.org\/uc\/item\/7902g5hh\" title=\"https:\/\/escholarship.org\/uc\/item\/7902g5hh\" target=\"_blank\">https:\/\/escholarship.org\/uc\/item\/7902g5hh<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.25436\/E23S3T\" title=\"Follow DOI:10.25436\/E23S3T\" target=\"_blank\">doi:10.25436\/E23S3T<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('49','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_inproceedings\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> Brunila, Mikael;  LaViolette, Jack<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('44','tp_links')\" style=\"cursor:pointer;\">WMDecompose: A Framework for Leveraging the Interpretable Properties of Word Mover's Distance in Sociocultural Analysis<\/a> <span class=\"tp_pub_type tp_  inproceedings\">Proceedings Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_booktitle\">The 5th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, <\/span><span class=\"tp_pub_additional_year\">2021<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_44\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('44','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_44\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('44','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_44\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('44','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_44\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@inproceedings{nokey,<br \/>\r\ntitle = {WMDecompose: A Framework for Leveraging the Interpretable Properties of Word Mover's Distance in Sociocultural Analysis},<br \/>\r\nauthor = {Mikael Brunila and Jack LaViolette},<br \/>\r\nurl = {https:\/\/arxiv.org\/abs\/2110.07330},<br \/>\r\nyear  = {2021},<br \/>\r\ndate = {2021-11-11},<br \/>\r\nurldate = {2021-11-11},<br \/>\r\nbooktitle = {The 5th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature},<br \/>\r\nabstract = {Despite the increasing popularity of NLP in the humanities and social sciences, advances in model performance and complexity have been accompanied by concerns about interpretability and explanatory power for sociocultural analysis. One popular model that balances complexity and legibility is Word Mover's Distance (WMD). Ostensibly adapted for its interpretability, WMD has nonetheless been used and further developed in ways which frequently discard its most interpretable aspect: namely, the word-level distances required for translating a set of words into another set of words. To address this apparent gap, we introduce WMDecompose: a model and Python library that 1) decomposes document-level distances into their constituent word-level distances, and 2) subsequently clusters words to induce thematic elements, such that useful lexical information is retained and summarized for analysis. To illustrate its potential in a social scientific context, we apply it to a longitudinal social media corpus to explore the interrelationship between conspiracy theories and conservative American discourses. Finally, because of the full WMD model's high time-complexity, we additionally suggest a method of sampling document pairs from large datasets in a reproducible way, with tight bounds that prevent extrapolation of unreliable results due to poor sampling practices. },<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {inproceedings}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('44','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_44\" style=\"display:none;\"><div class=\"tp_abstract_entry\">Despite the increasing popularity of NLP in the humanities and social sciences, advances in model performance and complexity have been accompanied by concerns about interpretability and explanatory power for sociocultural analysis. One popular model that balances complexity and legibility is Word Mover's Distance (WMD). Ostensibly adapted for its interpretability, WMD has nonetheless been used and further developed in ways which frequently discard its most interpretable aspect: namely, the word-level distances required for translating a set of words into another set of words. To address this apparent gap, we introduce WMDecompose: a model and Python library that 1) decomposes document-level distances into their constituent word-level distances, and 2) subsequently clusters words to induce thematic elements, such that useful lexical information is retained and summarized for analysis. To illustrate its potential in a social scientific context, we apply it to a longitudinal social media corpus to explore the interrelationship between conspiracy theories and conservative American discourses. Finally, because of the full WMD model's high time-complexity, we additionally suggest a method of sampling document pairs from large datasets in a reproducible way, with tight bounds that prevent extrapolation of unreliable results due to poor sampling practices. <\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('44','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_44\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"ai ai-arxiv\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/arxiv.org\/abs\/2110.07330\" title=\"https:\/\/arxiv.org\/abs\/2110.07330\" target=\"_blank\">https:\/\/arxiv.org\/abs\/2110.07330<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('44','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_inbook\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> McKenzie, Grant;  Adams, Benjamin<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('45','tp_links')\" style=\"cursor:pointer;\">Natural Language Processing in GIScience Applications<\/a> <span class=\"tp_pub_type tp_  inbook\">Book Chapter<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span> Wilson, John (Ed.): <span class=\"tp_pub_additional_booktitle\">The GIS&amp;T Body of Knowledge, <\/span><span class=\"tp_pub_additional_publisher\">University Consortium of Geographic Information Science, <\/span><span class=\"tp_pub_additional_year\">2021<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_resource_link\"><a id=\"tp_links_sh_45\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('45','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_45\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('45','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_45\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@inbook{McKenzie2021b,<br \/>\r\ntitle = {Natural Language Processing in GIScience Applications},<br \/>\r\nauthor = {Grant McKenzie and Benjamin Adams},<br \/>\r\neditor = {John Wilson},<br \/>\r\nurl = {https:\/\/grantmckenzie.com\/academics\/McKenzieUCGISBOK2021.pdf},<br \/>\r\nyear  = {2021},<br \/>\r\ndate = {2021-11-08},<br \/>\r\nurldate = {2021-11-08},<br \/>\r\nbooktitle = {The GIS&T Body of Knowledge},<br \/>\r\npublisher = {University Consortium of Geographic Information Science},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {inbook}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('45','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_45\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-file-pdf\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/grantmckenzie.com\/academics\/McKenzieUCGISBOK2021.pdf\" title=\"https:\/\/grantmckenzie.com\/academics\/McKenzieUCGISBOK2021.pdf\" target=\"_blank\">https:\/\/grantmckenzie.com\/academics\/McKenzieUCGISBOK2021.pdf<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('45','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_inproceedings\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> Chen, Emily;  McKenzie, Grant<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('43','tp_links')\" style=\"cursor:pointer;\">Mobility Response to COVID-19-related Restrictions in New York City<\/a> <span class=\"tp_pub_type tp_  inproceedings\">Proceedings Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_booktitle\">The 2nd ACM SIGSPATIAL International Workshop on Spatial Computing for Epidemiology (SpatialEpi'21), <\/span><span class=\"tp_pub_additional_publisher\">ACM, <\/span><span class=\"tp_pub_additional_year\">2021<\/span>, <span class=\"tp_pub_additional_issn\">ISSN: 98-1-4503-9119-1\/21\/11<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_43\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('43','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_43\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('43','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_43\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('43','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_43\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@inproceedings{ChenMcKenzie2021,<br \/>\r\ntitle = {Mobility Response to COVID-19-related Restrictions in New York City},<br \/>\r\nauthor = {Emily Chen and Grant McKenzie},<br \/>\r\nurl = {https:\/\/grantmckenzie.com\/academics\/ChenMcKenzie2021.pdf},<br \/>\r\ndoi = {10.1145\/3486633.3491094},<br \/>\r\nissn = {98-1-4503-9119-1\/21\/11},<br \/>\r\nyear  = {2021},<br \/>\r\ndate = {2021-11-02},<br \/>\r\nurldate = {2021-11-02},<br \/>\r\nbooktitle = {The 2nd ACM SIGSPATIAL International Workshop on Spatial Computing for Epidemiology (SpatialEpi'21)},<br \/>\r\npublisher = {ACM},<br \/>\r\nabstract = {The first case of the 2019 novel coronavirus was detected in the United States in January 2020, and since then, efforts to contain the virus, such as stay-at-home policies, have greatly restricted human mobility. While stay-at-home policies and concern over the virus contributed to an increase in time spent at home, little is known as to how a change in home dwell time varied by population. The work presented in this paper seeks to understand the relationships between levels of mobility and socioeconomic and demographics characteristics of communities within New York City from February to April 2020.  Through analyzing the factors that contributed to changes in home dwell time, this work aims to support policymakers and inform future strategies for infection mitigation. Findings from this research reinforce the need for physical distancing policies that acknowledge the existence of socioeconomic and demographic diversity between not only geographic regions in the U.S. but also within a single city. },<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {inproceedings}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('43','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_43\" style=\"display:none;\"><div class=\"tp_abstract_entry\">The first case of the 2019 novel coronavirus was detected in the United States in January 2020, and since then, efforts to contain the virus, such as stay-at-home policies, have greatly restricted human mobility. While stay-at-home policies and concern over the virus contributed to an increase in time spent at home, little is known as to how a change in home dwell time varied by population. The work presented in this paper seeks to understand the relationships between levels of mobility and socioeconomic and demographics characteristics of communities within New York City from February to April 2020.  Through analyzing the factors that contributed to changes in home dwell time, this work aims to support policymakers and inform future strategies for infection mitigation. Findings from this research reinforce the need for physical distancing policies that acknowledge the existence of socioeconomic and demographic diversity between not only geographic regions in the U.S. but also within a single city. <\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('43','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_43\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-file-pdf\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/grantmckenzie.com\/academics\/ChenMcKenzie2021.pdf\" title=\"https:\/\/grantmckenzie.com\/academics\/ChenMcKenzie2021.pdf\" target=\"_blank\">https:\/\/grantmckenzie.com\/academics\/ChenMcKenzie2021.pdf<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1145\/3486633.3491094\" title=\"Follow DOI:10.1145\/3486633.3491094\" target=\"_blank\">doi:10.1145\/3486633.3491094<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('43','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_inbook\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> McKenzie, Grant;  Baez, Carlos<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('47','tp_links')\" style=\"cursor:pointer;\">A Spatiotemporal approach to micromobility<\/a> <span class=\"tp_pub_type tp_  inbook\">Book Chapter<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span> Sigler, T.;  Corcoran, J. (Ed.): <span class=\"tp_pub_additional_booktitle\">A Modern Guide to the Urban Sharing Economy, <\/span><span class=\"tp_pub_additional_pages\">pp. 195-208, <\/span><span class=\"tp_pub_additional_publisher\">Elgar Publishing, <\/span><span class=\"tp_pub_additional_year\">2021<\/span>, <span class=\"tp_pub_additional_isbn\">ISBN: 978 1 78990 955 5<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_resource_link\"><a id=\"tp_links_sh_47\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('47','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_47\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('47','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_47\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@inbook{McKenzie2021d,<br \/>\r\ntitle = {A Spatiotemporal approach to micromobility},<br \/>\r\nauthor = {Grant McKenzie and Carlos Baez},<br \/>\r\neditor = {T. Sigler and J. Corcoran},<br \/>\r\nurl = {https:\/\/grantmckenzie.com\/academics\/mckenziebaez2021.pdf},<br \/>\r\nisbn = {978 1 78990 955 5},<br \/>\r\nyear  = {2021},<br \/>\r\ndate = {2021-09-01},<br \/>\r\nurldate = {2021-09-01},<br \/>\r\nbooktitle = {A Modern Guide to the Urban Sharing Economy},<br \/>\r\npages = {195-208},<br \/>\r\npublisher = {Elgar Publishing},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {inbook}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('47','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_47\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-file-pdf\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/grantmckenzie.com\/academics\/mckenziebaez2021.pdf\" title=\"https:\/\/grantmckenzie.com\/academics\/mckenziebaez2021.pdf\" target=\"_blank\">https:\/\/grantmckenzie.com\/academics\/mckenziebaez2021.pdf<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('47','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> McKenzie, Grant;  Romm, Daniel<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('42','tp_links')\" style=\"cursor:pointer;\">Measuring urban regional similarity through mobility signatures<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">Computers, Environment and Urban Systems, <\/span><span class=\"tp_pub_additional_volume\">vol. 89, <\/span><span class=\"tp_pub_additional_pages\">pp. 101684, <\/span><span class=\"tp_pub_additional_year\">2021<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_42\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('42','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_42\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('42','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_42\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('42','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_42\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{McKenzie2021,<br \/>\r\ntitle = {Measuring urban regional similarity through mobility signatures},<br \/>\r\nauthor = {Grant McKenzie and Daniel Romm},<br \/>\r\nurl = {https:\/\/grantmckenzie.com\/academics\/CitySim_2021.pdf<br \/>\r\nhttps:\/\/platial.science\/citysim\/<br \/>\r\nhttps:\/\/www.sciencedirect.com\/science\/article\/pii\/S0198971521000910},<br \/>\r\ndoi = {10.1016\/j.compenvurbsys.2021.101684},<br \/>\r\nyear  = {2021},<br \/>\r\ndate = {2021-09-01},<br \/>\r\njournal = {Computers, Environment and Urban Systems},<br \/>\r\nvolume = {89},<br \/>\r\npages = {101684},<br \/>\r\nabstract = {The task of identifying similar regions within and between cities is an important aspect of urban data science as well as applied domains such as real estate, tourism, and urban planning. Regional similarity is typically assessed through comparing socio-demographic variables, resource availability, or urban infrastructure. An essential dimension, often overlooked for this task, is the spatiotemporal mobility patterns of people within a city. In this work we present a novel approach to identifying regional similarity based on human mobility as proxied through micromobility trips. We use a dataset consisting of e-scooter trip origins and destinations for two major European cities that differ in population size and urban structure. Three dimensions of these data are used in modeling the spatial and temporal variability in movement between regions in cities, allowing us to compare regions through a mobility lens. The result is a parameterized similarity model and interactive web platform for comparing regions across different urban environments. The application of this model suggests that human mobility patterns are a quantifiable, unique, and appropriate characteristic through which to measure urban similarity.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('42','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_42\" style=\"display:none;\"><div class=\"tp_abstract_entry\">The task of identifying similar regions within and between cities is an important aspect of urban data science as well as applied domains such as real estate, tourism, and urban planning. Regional similarity is typically assessed through comparing socio-demographic variables, resource availability, or urban infrastructure. An essential dimension, often overlooked for this task, is the spatiotemporal mobility patterns of people within a city. In this work we present a novel approach to identifying regional similarity based on human mobility as proxied through micromobility trips. We use a dataset consisting of e-scooter trip origins and destinations for two major European cities that differ in population size and urban structure. Three dimensions of these data are used in modeling the spatial and temporal variability in movement between regions in cities, allowing us to compare regions through a mobility lens. The result is a parameterized similarity model and interactive web platform for comparing regions across different urban environments. The application of this model suggests that human mobility patterns are a quantifiable, unique, and appropriate characteristic through which to measure urban similarity.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('42','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_42\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-file-pdf\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/grantmckenzie.com\/academics\/CitySim_2021.pdf\" title=\"https:\/\/grantmckenzie.com\/academics\/CitySim_2021.pdf\" target=\"_blank\">https:\/\/grantmckenzie.com\/academics\/CitySim_2021.pdf<\/a><\/li><li><i class=\"fas fa-globe\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/platial.science\/citysim\/\" title=\"https:\/\/platial.science\/citysim\/\" target=\"_blank\">https:\/\/platial.science\/citysim\/<\/a><\/li><li><i class=\"fas fa-globe\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0198971521000910\" title=\"https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0198971521000910\" target=\"_blank\">https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0198971521000910<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1016\/j.compenvurbsys.2021.101684\" title=\"Follow DOI:10.1016\/j.compenvurbsys.2021.101684\" target=\"_blank\">doi:10.1016\/j.compenvurbsys.2021.101684<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('42','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><h3 class=\"tp_h3\" id=\"tp_h3_2020\">2020<\/h3><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> McKenzie, Grant;  Adams, Benjamin<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('41','tp_links')\" style=\"cursor:pointer;\">A country comparison of place-based activity response to COVID-19 policies<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">Applied Geography, <\/span><span class=\"tp_pub_additional_volume\">vol. 125, <\/span><span class=\"tp_pub_additional_number\">no. 2020, <\/span><span class=\"tp_pub_additional_pages\">pp. 102363, <\/span><span class=\"tp_pub_additional_year\">2020<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_41\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('41','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_41\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('41','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_41\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('41','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_41\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{McKenzie2020,<br \/>\r\ntitle = {A country comparison of place-based activity response to COVID-19 policies},<br \/>\r\nauthor = {Grant McKenzie and Benjamin Adams},<br \/>\r\nurl = {https:\/\/grantmckenzie.com\/academics\/McKenzieAdams2020.pdf},<br \/>\r\ndoi = {10.1016\/j.apgeog.2020.102363},<br \/>\r\nyear  = {2020},<br \/>\r\ndate = {2020-05-19},<br \/>\r\njournal = {Applied Geography},<br \/>\r\nvolume = {125},<br \/>\r\nnumber = {2020},<br \/>\r\npages = {102363},<br \/>\r\norganization = {arXiv.org},<br \/>\r\nabstract = {The emergence of the novel Coronavirus Disease in late 2019 (COVID-19) and subsequent pandemic led to an immense disruption in the daily lives of almost everyone on the planet.  Faced with the consequences of inaction, most national governments responded with policies that restricted the activities conducted by their inhabitants.  As schools and businesses shuttered, the mobility of these people decreased.  This reduction in mobility, and related activities, was recorded through ubiquitous location-enabled personal mobile devices.  Patterns emerged that varied by place-based activity.  In this work the differences in these place-based activity patterns are investigated across nations, specifically focusing on the relationship between government enacted policies and changes in community activity patterns.  We show that people's activity response to government action varies widely both across nations as well as regionally within them.  Three assessment measures are devised and the results correlate with a number of global indices.  We discuss these findings and the relationship between government action and residents' response.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('41','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_41\" style=\"display:none;\"><div class=\"tp_abstract_entry\">The emergence of the novel Coronavirus Disease in late 2019 (COVID-19) and subsequent pandemic led to an immense disruption in the daily lives of almost everyone on the planet.  Faced with the consequences of inaction, most national governments responded with policies that restricted the activities conducted by their inhabitants.  As schools and businesses shuttered, the mobility of these people decreased.  This reduction in mobility, and related activities, was recorded through ubiquitous location-enabled personal mobile devices.  Patterns emerged that varied by place-based activity.  In this work the differences in these place-based activity patterns are investigated across nations, specifically focusing on the relationship between government enacted policies and changes in community activity patterns.  We show that people's activity response to government action varies widely both across nations as well as regionally within them.  Three assessment measures are devised and the results correlate with a number of global indices.  We discuss these findings and the relationship between government action and residents' response.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('41','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_41\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-file-pdf\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/grantmckenzie.com\/academics\/McKenzieAdams2020.pdf\" title=\"https:\/\/grantmckenzie.com\/academics\/McKenzieAdams2020.pdf\" target=\"_blank\">https:\/\/grantmckenzie.com\/academics\/McKenzieAdams2020.pdf<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1016\/j.apgeog.2020.102363\" title=\"Follow DOI:10.1016\/j.apgeog.2020.102363\" target=\"_blank\">doi:10.1016\/j.apgeog.2020.102363<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('41','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> McKenzie, Grant<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('39','tp_links')\" style=\"cursor:pointer;\">Urban mobility in the sharing economy: A spatiotemporal comparison of shared mobility services<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">Computers, Environment and Urban Systems, <\/span><span class=\"tp_pub_additional_volume\">vol. 79, <\/span><span class=\"tp_pub_additional_pages\">pp. 101418, <\/span><span class=\"tp_pub_additional_year\">2020<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_39\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('39','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_39\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('39','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_39\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('39','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_39\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{McKenzieCEUS2019,<br \/>\r\ntitle = {Urban mobility in the sharing economy: A spatiotemporal comparison of shared mobility services},<br \/>\r\nauthor = {Grant McKenzie },<br \/>\r\nurl = {https:\/\/www.grantmckenzie.com\/academics\/McKenzie_CEUS2019.pdf},<br \/>\r\nyear  = {2020},<br \/>\r\ndate = {2020-01-01},<br \/>\r\njournal = {Computers, Environment and Urban Systems},<br \/>\r\nvolume = {79},<br \/>\r\npages = {101418},<br \/>\r\nabstract = {The influx of micro-mobility services, such as dockless scooter-share and e-bikes, in many cities are contributing to a substantial change in urban transportation with adoption rates reminiscent of other shared-mobility services, such as ride-hailing, years prior.  Touted as a solution to the last mile problem, a multitude of micro-mobility companies have situated themselves in urban centers promising low cost alternative transportation options for short, urban travel.  The rapid arrival of these companies, however, has left little time for city officials, transportation planners, and citizens to assess the demand for these services and compare them to existing transportation options.  In this work, we investigate two key aspects of these micro-mobility services. First, we identify the spatial and temporal differences between these mobility companies and highlight the nuanced differences in usage patterns.  Second, we compare these new services to an existing mode of transportation, namely automobile-based ride-hailing, with regards to differences in travel time within a city.  The results of these analyses indicate that while many micro-mobility companies are spatiotemporally similar, there are notable differences in where and when these services are used.  Similarly, we find that automobile travel is not always the fastest means of transportation within an urban setting.  During periods of heavy traffic congestion, e.g., rush hour, micro-mobility services offer a faster means of travel within the city.  The findings presented in this work offer evidence on which to inform urban planning and transportation policy with respect to shared mobility services, free floating vehicles, and alternative urban transportation.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('39','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_39\" style=\"display:none;\"><div class=\"tp_abstract_entry\">The influx of micro-mobility services, such as dockless scooter-share and e-bikes, in many cities are contributing to a substantial change in urban transportation with adoption rates reminiscent of other shared-mobility services, such as ride-hailing, years prior.  Touted as a solution to the last mile problem, a multitude of micro-mobility companies have situated themselves in urban centers promising low cost alternative transportation options for short, urban travel.  The rapid arrival of these companies, however, has left little time for city officials, transportation planners, and citizens to assess the demand for these services and compare them to existing transportation options.  In this work, we investigate two key aspects of these micro-mobility services. First, we identify the spatial and temporal differences between these mobility companies and highlight the nuanced differences in usage patterns.  Second, we compare these new services to an existing mode of transportation, namely automobile-based ride-hailing, with regards to differences in travel time within a city.  The results of these analyses indicate that while many micro-mobility companies are spatiotemporally similar, there are notable differences in where and when these services are used.  Similarly, we find that automobile travel is not always the fastest means of transportation within an urban setting.  During periods of heavy traffic congestion, e.g., rush hour, micro-mobility services offer a faster means of travel within the city.  The findings presented in this work offer evidence on which to inform urban planning and transportation policy with respect to shared mobility services, free floating vehicles, and alternative urban transportation.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('39','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_39\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-file-pdf\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/www.grantmckenzie.com\/academics\/McKenzie_CEUS2019.pdf\" title=\"https:\/\/www.grantmckenzie.com\/academics\/McKenzie_CEUS2019.pdf\" target=\"_blank\">https:\/\/www.grantmckenzie.com\/academics\/McKenzie_CEUS2019.pdf<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('39','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><h3 class=\"tp_h3\" id=\"tp_h3_2019\">2019<\/h3><div class=\"tp_publication tp_publication_inproceedings\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> McKenzie, Grant<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('40','tp_links')\" style=\"cursor:pointer;\">Shared micro-mobility patterns as measures of city similarity<\/a> <span class=\"tp_pub_type tp_  inproceedings\">Proceedings Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span>van Kreveld, Marc;  Speckmann, Bettina;  Stroila, Matei;  Trajcevski, Goce (Ed.): <span class=\"tp_pub_additional_booktitle\">1st ACM SIGSPATIAL International Workshop on Computing with Multifaceted Movement Data (MOVE++ 2019) in conjunction with the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems., <\/span><span class=\"tp_pub_additional_publisher\">ACM, <\/span><span class=\"tp_pub_additional_year\">2019<\/span>, <span class=\"tp_pub_additional_isbn\">ISBN: 78-1-4503-6951-0\/19\/11<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_40\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('40','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_40\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('40','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_40\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('40','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_40\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@inproceedings{Move2019,<br \/>\r\ntitle = {Shared micro-mobility patterns as measures of city similarity},<br \/>\r\nauthor = {Grant McKenzie },<br \/>\r\neditor = {Marc van Kreveld and Bettina Speckmann and Matei Stroila and Goce Trajcevski},<br \/>\r\nurl = {https:\/\/grantmckenzie.com\/academics\/McKenzie_Move2019.pdf},<br \/>\r\ndoi = {https:\/\/doi.org\/10.1145\/3356392.3365221},<br \/>\r\nisbn = {78-1-4503-6951-0\/19\/11},<br \/>\r\nyear  = {2019},<br \/>\r\ndate = {2019-11-05},<br \/>\r\nbooktitle = {1st ACM SIGSPATIAL International Workshop on Computing with Multifaceted Movement Data (MOVE++ 2019) in conjunction with the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems.},<br \/>\r\npublisher = {ACM},<br \/>\r\nabstract = {Micro-mobility services, such as dockless e-scooters and e-bikes, are inundating urban centers around the world.  The mass adoption of these services, and ubiquity of the companies operating them, offer a unique opportunity through which to compare cities.  In this position paper, a series of spatiotemporal measures are proposed based on activity data collected from shared micro-mobility services.  The purpose of this paper is to identify a number of ways that these new mobility services can serve to augment existing city similarity approaches.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {inproceedings}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('40','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_40\" style=\"display:none;\"><div class=\"tp_abstract_entry\">Micro-mobility services, such as dockless e-scooters and e-bikes, are inundating urban centers around the world.  The mass adoption of these services, and ubiquity of the companies operating them, offer a unique opportunity through which to compare cities.  In this position paper, a series of spatiotemporal measures are proposed based on activity data collected from shared micro-mobility services.  The purpose of this paper is to identify a number of ways that these new mobility services can serve to augment existing city similarity approaches.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('40','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_40\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-file-pdf\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/grantmckenzie.com\/academics\/McKenzie_Move2019.pdf\" title=\"https:\/\/grantmckenzie.com\/academics\/McKenzie_Move2019.pdf\" target=\"_blank\">https:\/\/grantmckenzie.com\/academics\/McKenzie_Move2019.pdf<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/https:\/\/doi.org\/10.1145\/3356392.3365221\" title=\"Follow DOI:https:\/\/doi.org\/10.1145\/3356392.3365221\" target=\"_blank\">doi:https:\/\/doi.org\/10.1145\/3356392.3365221<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('40','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> McKenzie, Grant<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('7','tp_links')\" style=\"cursor:pointer;\">Spatiotemporal comparative analysis of scooter-share and bike-share usage patterns in Washington, D.C.<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">Journal of Transport Geography, <\/span><span class=\"tp_pub_additional_volume\">vol. 78, <\/span><span class=\"tp_pub_additional_pages\">pp. 19-28, <\/span><span class=\"tp_pub_additional_year\">2019<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_7\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('7','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_7\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('7','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_7\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('7','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_7\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{80,<br \/>\r\ntitle = {Spatiotemporal comparative analysis of scooter-share and bike-share usage patterns in Washington, D.C.},<br \/>\r\nauthor = {Grant McKenzie},<br \/>\r\nurl = {https:\/\/www.grantmckenzie.com\/academics\/McKenzie_JTG2019.pdf},<br \/>\r\ndoi = {10.1016\/j.jtrangeo.2019.05.007},<br \/>\r\nyear  = {2019},<br \/>\r\ndate = {2019-06-01},<br \/>\r\njournal = {Journal of Transport Geography},<br \/>\r\nvolume = {78},<br \/>\r\npages = {19-28},<br \/>\r\nchapter = {19},<br \/>\r\nabstract = {The United States is currently in the midst of a micro-mobility revolution of sorts. Almost overnight, U.S. cities have been inundated with short-term rental scooters owned and operated by start-up companies promising a disruption to the urban transportation status-quo. These scooter-share services are presented as a dockless alternative to traditionally government-funded, docking station-based bike-sharing programs. Given the rapid rise of electric scooter companies, and how little is known about their operations, there is pressing public interest in understanding the impact of these transportation-sharing platforms. By exploring the nuanced spatial and temporal activity patterns of each of these platforms, this research identifies differences and similarities between dockless e-scooters and existing bike-sharing services. The findings from this research contribute to our understanding of urban transportation behavior and differences within mobility platforms.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('7','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_7\" style=\"display:none;\"><div class=\"tp_abstract_entry\">The United States is currently in the midst of a micro-mobility revolution of sorts. Almost overnight, U.S. cities have been inundated with short-term rental scooters owned and operated by start-up companies promising a disruption to the urban transportation status-quo. These scooter-share services are presented as a dockless alternative to traditionally government-funded, docking station-based bike-sharing programs. Given the rapid rise of electric scooter companies, and how little is known about their operations, there is pressing public interest in understanding the impact of these transportation-sharing platforms. By exploring the nuanced spatial and temporal activity patterns of each of these platforms, this research identifies differences and similarities between dockless e-scooters and existing bike-sharing services. The findings from this research contribute to our understanding of urban transportation behavior and differences within mobility platforms.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('7','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_7\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-file-pdf\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/www.grantmckenzie.com\/academics\/McKenzie_JTG2019.pdf\" title=\"https:\/\/www.grantmckenzie.com\/academics\/McKenzie_JTG2019.pdf\" target=\"_blank\">https:\/\/www.grantmckenzie.com\/academics\/McKenzie_JTG2019.pdf<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1016\/j.jtrangeo.2019.05.007\" title=\"Follow DOI:10.1016\/j.jtrangeo.2019.05.007\" target=\"_blank\">doi:10.1016\/j.jtrangeo.2019.05.007<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('7','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> McKenzie, Grant;  Slind, Todd R<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('8','tp_links')\" style=\"cursor:pointer;\">A user-generated data based approach to enhancing location prediction of financial services in sub-Saharan Africa<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">Applied Geography, <\/span><span class=\"tp_pub_additional_year\">2019<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_8\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('8','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_8\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('8','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_8\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('8','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_8\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{71,<br \/>\r\ntitle = {A user-generated data based approach to enhancing location prediction of financial services in sub-Saharan Africa},<br \/>\r\nauthor = {Grant McKenzie and Todd R Slind},<br \/>\r\nurl = {https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0143622818302078},<br \/>\r\ndoi = {10.1016\/j.apgeog.2019.02.005},<br \/>\r\nyear  = {2019},<br \/>\r\ndate = {2019-01-01},<br \/>\r\njournal = {Applied Geography},<br \/>\r\nabstract = {The recent increase in user-generated content and social media adoption in developing countries offers an unprecedented opportunity to better understand the accessibility and spatial distribution of financial services in sub-Saharan Africa. Financial inclusion has been identified as a priority by multiple agencies in the region and on-the-ground efforts are currently underway to identify previously unknown financial access points in numerous developing African countries. Existing techniques for estimating the location of these access points rely on spatial analysis of often outdated or unsuitable publicly available datasets such as population density, road networks, etc. as well as expensive and time consuming surveys of locals in the region. In this work we propose an approach to augment existing spatial data analysis techniques through the inclusion of user-generated geo-content and geo-social media data. Though a comparison of standard regression models and machine learning techniques, this work proposes the use of alternative data sources to build prediction models for identifying financial access locations in countries where current estimation models are insufficient. Through a better understanding of geospatial distribution patterns this work aims at reducing data acquisition costs and providing decision makers with critical data more quickly and efficiently. Finally, we present a mobile application build on the outcomes of this analysis that is currently being used to better inform on-the-ground data collection efforts.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('8','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_8\" style=\"display:none;\"><div class=\"tp_abstract_entry\">The recent increase in user-generated content and social media adoption in developing countries offers an unprecedented opportunity to better understand the accessibility and spatial distribution of financial services in sub-Saharan Africa. Financial inclusion has been identified as a priority by multiple agencies in the region and on-the-ground efforts are currently underway to identify previously unknown financial access points in numerous developing African countries. Existing techniques for estimating the location of these access points rely on spatial analysis of often outdated or unsuitable publicly available datasets such as population density, road networks, etc. as well as expensive and time consuming surveys of locals in the region. In this work we propose an approach to augment existing spatial data analysis techniques through the inclusion of user-generated geo-content and geo-social media data. Though a comparison of standard regression models and machine learning techniques, this work proposes the use of alternative data sources to build prediction models for identifying financial access locations in countries where current estimation models are insufficient. Through a better understanding of geospatial distribution patterns this work aims at reducing data acquisition costs and providing decision makers with critical data more quickly and efficiently. Finally, we present a mobile application build on the outcomes of this analysis that is currently being used to better inform on-the-ground data collection efforts.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('8','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_8\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-globe\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0143622818302078\" title=\"https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0143622818302078\" target=\"_blank\">https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0143622818302078<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1016\/j.apgeog.2019.02.005\" title=\"Follow DOI:10.1016\/j.apgeog.2019.02.005\" target=\"_blank\">doi:10.1016\/j.apgeog.2019.02.005<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('8','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><h3 class=\"tp_h3\" id=\"tp_h3_2018\">2018<\/h3><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> McKenzie, Grant;  Liu, Zheng;  Hu, Yingjie;  Lee, Myeong<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('13','tp_links')\" style=\"cursor:pointer;\">Identifying urban neighborhood names through user-contributed online property listings<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">ISPRS International Journal of Geo-Information, <\/span><span class=\"tp_pub_additional_year\">2018<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_13\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('13','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_13\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('13','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_13\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('13','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_13\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{65,<br \/>\r\ntitle = {Identifying urban neighborhood names through user-contributed online property listings},<br \/>\r\nauthor = {Grant McKenzie and Zheng Liu and Yingjie Hu and Myeong Lee},<br \/>\r\nurl = {https:\/\/grantdmckenzie.com\/academics\/McKenzie_Neighborhoods2018.pdf},<br \/>\r\nyear  = {2018},<br \/>\r\ndate = {2018-10-01},<br \/>\r\njournal = {ISPRS International Journal of Geo-Information},<br \/>\r\nabstract = {Neighborhoods are vaguely defined, localized regions that share similar characteristics. They are most often defined, delineated, and named by the citizens that inhabit them rather than municipal government or commercial agencies. The names of these neighborhoods play an important role as a basis for community and sociodemographic identity, geographic communication, and historical context. In this work we take a data-driven approach to identifying neighborhood names based on the geospatial properties of user-contributed rental listings. Through a random forest ensemble learning model applied to a set of spatial statistics for all n-grams in listing descriptions, we show that neighborhood names can be uniquely identified within urban settings. We train a model based on data from Washington, DC and test it on listings in Seattle, WA and Montreal, QC. The results indicate that a model trained on housing data from one city can successfully identify neighborhood names in another. In addition, our approach identifies less common neighborhood names and suggestions alternative or potentially new names in each city. These findings represent a first step in the process of urban neighborhood identification and delineation.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('13','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_13\" style=\"display:none;\"><div class=\"tp_abstract_entry\">Neighborhoods are vaguely defined, localized regions that share similar characteristics. They are most often defined, delineated, and named by the citizens that inhabit them rather than municipal government or commercial agencies. The names of these neighborhoods play an important role as a basis for community and sociodemographic identity, geographic communication, and historical context. In this work we take a data-driven approach to identifying neighborhood names based on the geospatial properties of user-contributed rental listings. Through a random forest ensemble learning model applied to a set of spatial statistics for all n-grams in listing descriptions, we show that neighborhood names can be uniquely identified within urban settings. We train a model based on data from Washington, DC and test it on listings in Seattle, WA and Montreal, QC. The results indicate that a model trained on housing data from one city can successfully identify neighborhood names in another. In addition, our approach identifies less common neighborhood names and suggestions alternative or potentially new names in each city. These findings represent a first step in the process of urban neighborhood identification and delineation.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('13','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_13\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-file-pdf\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/grantdmckenzie.com\/academics\/McKenzie_Neighborhoods2018.pdf\" title=\"https:\/\/grantdmckenzie.com\/academics\/McKenzie_Neighborhoods2018.pdf\" target=\"_blank\">https:\/\/grantdmckenzie.com\/academics\/McKenzie_Neighborhoods2018.pdf<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('13','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_conference\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> McKenzie, Grant<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('11','tp_links')\" style=\"cursor:pointer;\">Docked vs. Dockless Bike-sharing: Contrasting Spatiotemporal Patterns<\/a> <span class=\"tp_pub_type tp_  conference\">Conference<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_booktitle\">The 10th International Conference on Geographic Information Science, <\/span><span class=\"tp_pub_additional_organization\">Schloss Dagstuhl <\/span><span class=\"tp_pub_additional_publisher\">Schloss Dagstuhl, <\/span><span class=\"tp_pub_additional_address\">Melbourne, Australia, <\/span><span class=\"tp_pub_additional_year\">2018<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_11\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('11','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_11\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('11','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_11\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('11','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_11\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@conference{57,<br \/>\r\ntitle = {Docked vs. Dockless Bike-sharing: Contrasting Spatiotemporal Patterns},<br \/>\r\nauthor = {Grant McKenzie},<br \/>\r\nurl = {http:\/\/www.grantmckenzie.com\/academics\/Dockless2018.pdf},<br \/>\r\ndoi = {10.4230\/LIPIcs.GIScience.2018.64},<br \/>\r\nyear  = {2018},<br \/>\r\ndate = {2018-08-01},<br \/>\r\nbooktitle = {The 10th International Conference on Geographic Information Science},<br \/>\r\npublisher = {Schloss Dagstuhl},<br \/>\r\naddress = {Melbourne, Australia},<br \/>\r\norganization = {Schloss Dagstuhl},<br \/>\r\nabstract = {U.S. urban centers are currently experiencing explosive growth in commercial dockless bike-sharing services. Tens of thousands of bikes have shown up across the country in recent months providing limited time for municipal governments to set regulations or assess their impact on government-funded dock-based bike-sharing programs. Washington, D.C. offers an unprecedented opportunity to examine the activity patterns of both docked and dockless bike-sharing services given the history of bike-sharing in the city and the recent availability of dockless bike data. This work presents an exploratory step in understanding how dockless bike-sharing services are being used within a city and the ways in which the activity patterns differ from traditional dock station-based programs.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {conference}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('11','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_11\" style=\"display:none;\"><div class=\"tp_abstract_entry\">U.S. urban centers are currently experiencing explosive growth in commercial dockless bike-sharing services. Tens of thousands of bikes have shown up across the country in recent months providing limited time for municipal governments to set regulations or assess their impact on government-funded dock-based bike-sharing programs. Washington, D.C. offers an unprecedented opportunity to examine the activity patterns of both docked and dockless bike-sharing services given the history of bike-sharing in the city and the recent availability of dockless bike data. This work presents an exploratory step in understanding how dockless bike-sharing services are being used within a city and the ways in which the activity patterns differ from traditional dock station-based programs.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('11','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_11\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-file-pdf\"><\/i><a class=\"tp_pub_list\" href=\"http:\/\/www.grantmckenzie.com\/academics\/Dockless2018.pdf\" title=\"http:\/\/www.grantmckenzie.com\/academics\/Dockless2018.pdf\" target=\"_blank\">http:\/\/www.grantmckenzie.com\/academics\/Dockless2018.pdf<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.4230\/LIPIcs.GIScience.2018.64\" title=\"Follow DOI:10.4230\/LIPIcs.GIScience.2018.64\" target=\"_blank\">doi:10.4230\/LIPIcs.GIScience.2018.64<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('11','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_conference\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> McKenzie, Grant;  Janowicz, Krzysztof<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('15','tp_links')\" style=\"cursor:pointer;\">OpenPOI: An Open Place of Interest Platform<\/a> <span class=\"tp_pub_type tp_  conference\">Conference<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_booktitle\">The 10th International Conference on Geographic Information Science, <\/span><span class=\"tp_pub_additional_organization\">Schloss Dagstuhl <\/span><span class=\"tp_pub_additional_publisher\">Schloss Dagstuhl, <\/span><span class=\"tp_pub_additional_address\">Melbourne, Australia, <\/span><span class=\"tp_pub_additional_year\">2018<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_15\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('15','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_15\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('15','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_15\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('15','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_15\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@conference{56,<br \/>\r\ntitle = {OpenPOI: An Open Place of Interest Platform},<br \/>\r\nauthor = {Grant McKenzie and Krzysztof Janowicz},<br \/>\r\nurl = {http:\/\/www.grantmckenzie.com\/academics\/OpenPOI2018.pdf},<br \/>\r\ndoi = {10.4230\/LIPIcs.GIScience.2018.65},<br \/>\r\nyear  = {2018},<br \/>\r\ndate = {2018-08-01},<br \/>\r\nbooktitle = {The 10th International Conference on Geographic Information Science},<br \/>\r\npublisher = {Schloss Dagstuhl},<br \/>\r\naddress = {Melbourne, Australia},<br \/>\r\norganization = {Schloss Dagstuhl},<br \/>\r\nabstract = {Places of Interest (POI) are a principal component of how human behavior is captured in todaytextquoterights geographic information. Increasingly, access to POI datasets are being restricted -- even silo-ed -- for commercial use, with vendors often impeding access to the very users that contribute the data. Open mapping platforms such as OpenStreetMap (OSM) offer access to a plethora of geospatial data though they can be limited in the attribute resolution or range of information associated with the data. Nuanced descriptive information associated with POI, e.g., ambience, are not captured by such platforms. Furthermore, interactions with a POI, such as checking in, or recommending a menu item, are inherently place-based concepts. Many of these interactions occur with high temporal volatility that involves frequent interaction with a platform, arguably inappropriate for the textquotelefttextquoteleftchangesettextquoterighttextquoteright model adopted by OSM and related datasets. In this short paper we propose OpenPOI, an open platform for storing, serving, and interacting with places of interests and the activities they afford.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {conference}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('15','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_15\" style=\"display:none;\"><div class=\"tp_abstract_entry\">Places of Interest (POI) are a principal component of how human behavior is captured in todaytextquoterights geographic information. Increasingly, access to POI datasets are being restricted -- even silo-ed -- for commercial use, with vendors often impeding access to the very users that contribute the data. Open mapping platforms such as OpenStreetMap (OSM) offer access to a plethora of geospatial data though they can be limited in the attribute resolution or range of information associated with the data. Nuanced descriptive information associated with POI, e.g., ambience, are not captured by such platforms. Furthermore, interactions with a POI, such as checking in, or recommending a menu item, are inherently place-based concepts. Many of these interactions occur with high temporal volatility that involves frequent interaction with a platform, arguably inappropriate for the textquotelefttextquoteleftchangesettextquoterighttextquoteright model adopted by OSM and related datasets. In this short paper we propose OpenPOI, an open platform for storing, serving, and interacting with places of interests and the activities they afford.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('15','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_15\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-file-pdf\"><\/i><a class=\"tp_pub_list\" href=\"http:\/\/www.grantmckenzie.com\/academics\/OpenPOI2018.pdf\" title=\"http:\/\/www.grantmckenzie.com\/academics\/OpenPOI2018.pdf\" target=\"_blank\">http:\/\/www.grantmckenzie.com\/academics\/OpenPOI2018.pdf<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.4230\/LIPIcs.GIScience.2018.65\" title=\"Follow DOI:10.4230\/LIPIcs.GIScience.2018.65\" target=\"_blank\">doi:10.4230\/LIPIcs.GIScience.2018.65<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('15','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> McKenzie, Grant;  Adams, Benjamin<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('10','tp_links')\" style=\"cursor:pointer;\">A data-driven approach to exploring similarities of tourist attractions through online reviews<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">Journal of Location Based Services, <\/span><span class=\"tp_pub_additional_volume\">vol. 12, <\/span><span class=\"tp_pub_additional_pages\">pp. 94-118, <\/span><span class=\"tp_pub_additional_year\">2018<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_10\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('10','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_10\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('10','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_10\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('10','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_10\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{59,<br \/>\r\ntitle = {A data-driven approach to exploring similarities of tourist attractions through online reviews},<br \/>\r\nauthor = {Grant McKenzie and Benjamin Adams},<br \/>\r\nurl = {http:\/\/www.grantmckenzie.com\/academics\/McKenzieAdams_Tourism2018.pdf},<br \/>\r\nyear  = {2018},<br \/>\r\ndate = {2018-07-01},<br \/>\r\njournal = {Journal of Location Based Services},<br \/>\r\nvolume = {12},<br \/>\r\npages = {94-118},<br \/>\r\nchapter = {94},<br \/>\r\nabstract = {The motivation for tourists to visit a city is often driven by the uniqueness of the attractions accessible within the region. The draw to these locations varies by visitor as some travelers are interested in a single specific attraction while others prefer thematic travel. Tourists today have access to detailed experiences of other visitors to these locations in the form of user-contributed text reviews, opinions, photographs, and videos, all contributed through online tourism platforms. The data available through these platforms offer a unique opportunity to examine the similarities and difference between these attractions, their cities, and the visitors that contribute the reviews. In this work we take a data-driven approach to assessing similarity through textual analysis of user-contributed reviews, uncovering nuanced differences and similarities in the ways that reviewers write about attractions and cities.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('10','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_10\" style=\"display:none;\"><div class=\"tp_abstract_entry\">The motivation for tourists to visit a city is often driven by the uniqueness of the attractions accessible within the region. The draw to these locations varies by visitor as some travelers are interested in a single specific attraction while others prefer thematic travel. Tourists today have access to detailed experiences of other visitors to these locations in the form of user-contributed text reviews, opinions, photographs, and videos, all contributed through online tourism platforms. The data available through these platforms offer a unique opportunity to examine the similarities and difference between these attractions, their cities, and the visitors that contribute the reviews. In this work we take a data-driven approach to assessing similarity through textual analysis of user-contributed reviews, uncovering nuanced differences and similarities in the ways that reviewers write about attractions and cities.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('10','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_10\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-file-pdf\"><\/i><a class=\"tp_pub_list\" href=\"http:\/\/www.grantmckenzie.com\/academics\/McKenzieAdams_Tourism2018.pdf\" title=\"http:\/\/www.grantmckenzie.com\/academics\/McKenzieAdams_Tourism2018.pdf\" target=\"_blank\">http:\/\/www.grantmckenzie.com\/academics\/McKenzieAdams_Tourism2018.pdf<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('10','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> Fu, Cheng;  McKenzie, Grant;  Frias-Martinez, Vanessa;  Stewart, Kathleen<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('12','tp_links')\" style=\"cursor:pointer;\">Identifying spatiotemporal urban activities through linguistic signatures<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">Computers, Environment and Urban Systems, <\/span><span class=\"tp_pub_additional_year\">2018<\/span>, <span class=\"tp_pub_additional_issn\">ISSN: 0198-9715<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_12\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('12','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_12\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('12','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_12\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('12','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_12\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{63,<br \/>\r\ntitle = {Identifying spatiotemporal urban activities through linguistic signatures},<br \/>\r\nauthor = {Cheng Fu and Grant McKenzie and Vanessa Frias-Martinez and Kathleen Stewart},<br \/>\r\nurl = {https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0198971517303472},<br \/>\r\ndoi = {10.1016\/j.compenvurbsys.2018.07.003},<br \/>\r\nissn = {0198-9715},<br \/>\r\nyear  = {2018},<br \/>\r\ndate = {2018-07-01},<br \/>\r\njournal = {Computers, Environment and Urban Systems},<br \/>\r\nabstract = {Identifying the activities that individuals conduct in a city is key to understanding urban dynamics. It is difficult, however, to identify different human activities on a large scale without incurring significant costs. This study focuses on modeling the spatiotemporal patterns of different activity types within cities by employing user-contributed, geosocial content as a proxy for human activities. In this work, we use linguistic topic modeling to analyze georeferenced twitter data in order to differentiate different activity types. We then examine the spatial and temporal patterns of the derived activity types in three U.S. cities: Baltimore, MD., Washington, D.C., and New York City, NY. The linguistic patterns reflect the spatiotemporal context of the places where the social media content is posted. We further construct a method to link what people post online to the activities conducted within a city. We then use these derived activities to profile the characteristics of neighborhoods in the three cities, and apply the activity signatures to discover similar neighborhoods both within and between the cities. This approach represents a novel activity-based method for assessing similarity between neighborhoods.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('12','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_12\" style=\"display:none;\"><div class=\"tp_abstract_entry\">Identifying the activities that individuals conduct in a city is key to understanding urban dynamics. It is difficult, however, to identify different human activities on a large scale without incurring significant costs. This study focuses on modeling the spatiotemporal patterns of different activity types within cities by employing user-contributed, geosocial content as a proxy for human activities. In this work, we use linguistic topic modeling to analyze georeferenced twitter data in order to differentiate different activity types. We then examine the spatial and temporal patterns of the derived activity types in three U.S. cities: Baltimore, MD., Washington, D.C., and New York City, NY. The linguistic patterns reflect the spatiotemporal context of the places where the social media content is posted. We further construct a method to link what people post online to the activities conducted within a city. We then use these derived activities to profile the characteristics of neighborhoods in the three cities, and apply the activity signatures to discover similar neighborhoods both within and between the cities. This approach represents a novel activity-based method for assessing similarity between neighborhoods.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('12','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_12\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-globe\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0198971517303472\" title=\"https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0198971517303472\" target=\"_blank\">https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0198971517303472<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1016\/j.compenvurbsys.2018.07.003\" title=\"Follow DOI:10.1016\/j.compenvurbsys.2018.07.003\" target=\"_blank\">doi:10.1016\/j.compenvurbsys.2018.07.003<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('12','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> Adams, Benjamin;  McKenzie, Grant<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('9','tp_links')\" style=\"cursor:pointer;\">Crowdsourcing the Character of a Place: Character-Level Convolutional Networks for Multilingual Geographic Text Classification<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">Transactions in GIS, <\/span><span class=\"tp_pub_additional_year\">2018<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_9\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('9','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_9\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('9','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_9\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('9','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_9\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{46,<br \/>\r\ntitle = {Crowdsourcing the Character of a Place: Character-Level Convolutional Networks for Multilingual Geographic Text Classification},<br \/>\r\nauthor = {Benjamin Adams and Grant McKenzie},<br \/>\r\nurl = {http:\/\/www.grantmckenzie.com\/academics\/CharacterOfPlace_2017.pdf},<br \/>\r\ndoi = {10.1111\/tgis.12317},<br \/>\r\nyear  = {2018},<br \/>\r\ndate = {2018-01-01},<br \/>\r\njournal = {Transactions in GIS},<br \/>\r\nabstract = {This article presents a new character-level convolutional neural network model that can classify multilingual text written using any character set that can be encoded with UTF-8, a standard and widely used 8-bit character encoding. For geographic classification of text, we demonstrate that this approach is competitive with state-of-the-art word-based text classification methods. The model was tested on four crowdsourced data sets made up of Wikipedia articles, online travel blogs, Geonames toponyms, and Twitter posts. Unlike word-based methods, which require data cleaning and pre-processing, the proposed model works for any language without modification and with classification accuracy comparable to existing methods. Using a synthetic data set with introduced character-level errors, we show it is more robust to noise than word-level classification algorithms. The results indicate that UTF-8 character-level convolutional neural networks are a promising technique for georeferencing noisy text, such as found in colloquial social media posts and texts scanned with optical character recognition. However, word-based methods currently require less computation time to train, so are currently preferable for classifying well-formatted and cleaned texts in single languages.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('9','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_9\" style=\"display:none;\"><div class=\"tp_abstract_entry\">This article presents a new character-level convolutional neural network model that can classify multilingual text written using any character set that can be encoded with UTF-8, a standard and widely used 8-bit character encoding. For geographic classification of text, we demonstrate that this approach is competitive with state-of-the-art word-based text classification methods. The model was tested on four crowdsourced data sets made up of Wikipedia articles, online travel blogs, Geonames toponyms, and Twitter posts. Unlike word-based methods, which require data cleaning and pre-processing, the proposed model works for any language without modification and with classification accuracy comparable to existing methods. Using a synthetic data set with introduced character-level errors, we show it is more robust to noise than word-level classification algorithms. The results indicate that UTF-8 character-level convolutional neural networks are a promising technique for georeferencing noisy text, such as found in colloquial social media posts and texts scanned with optical character recognition. However, word-based methods currently require less computation time to train, so are currently preferable for classifying well-formatted and cleaned texts in single languages.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('9','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_9\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-file-pdf\"><\/i><a class=\"tp_pub_list\" href=\"http:\/\/www.grantmckenzie.com\/academics\/CharacterOfPlace_2017.pdf\" title=\"http:\/\/www.grantmckenzie.com\/academics\/CharacterOfPlace_2017.pdf\" target=\"_blank\">http:\/\/www.grantmckenzie.com\/academics\/CharacterOfPlace_2017.pdf<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1111\/tgis.12317\" title=\"Follow DOI:10.1111\/tgis.12317\" target=\"_blank\">doi:10.1111\/tgis.12317<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('9','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> Hu, Yingjie;  Mao, Huina;  McKenzie, Grant<\/p><p class=\"tp_pub_title\">A Natural Language Processing and Geospatial Clustering Framework for Harvesting Local Place Names from Geotagged Housing Advertisements <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">International Journal of Geographical Information Science, <\/span><span class=\"tp_pub_additional_year\">2018<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_14\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('14','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_14\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('14','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_14\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{50,<br \/>\r\ntitle = {A Natural Language Processing and Geospatial Clustering Framework for Harvesting Local Place Names from Geotagged Housing Advertisements},<br \/>\r\nauthor = {Yingjie Hu and Huina Mao and Grant McKenzie},<br \/>\r\nyear  = {2018},<br \/>\r\ndate = {2018-01-01},<br \/>\r\njournal = {International Journal of Geographical Information Science},<br \/>\r\nabstract = {Local place names are frequently used by residents living in a geographic region. Such place names may not be recorded in existing gazetteers, due to their vernacular nature, relative insignificance to a gazetteer covering a large area (e.g., the entire world), recent establishment (e.g., the name of a newly-opened shopping center), or other reasons. While not always recorded, local place names play important roles in many applications, from supporting public participation in urban planning to locating victims in disaster response. In this paper, we propose a computational framework for harvesting local place names from geotagged housing advertisements. We make use of those advertisements posted on local-oriented websites, such as Craigslist, where local place names are often mentioned. The proposed framework consists of two stages: natural language processing (NLP) and geospatial clustering. The NLP stage examines the textual content of housing advertisements, and extracts place name candidates. The geospatial stage focuses on the coordinates associated with the extracted place name candidates, and performs multi-scale geospatial clustering to filter out the non-place names. We evaluate our framework by comparing its performance with those of six baselines. We also compare our result with four existing gazetteers to demonstrate the not-yet-recorded local place names discovered by our framework.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('14','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_14\" style=\"display:none;\"><div class=\"tp_abstract_entry\">Local place names are frequently used by residents living in a geographic region. Such place names may not be recorded in existing gazetteers, due to their vernacular nature, relative insignificance to a gazetteer covering a large area (e.g., the entire world), recent establishment (e.g., the name of a newly-opened shopping center), or other reasons. While not always recorded, local place names play important roles in many applications, from supporting public participation in urban planning to locating victims in disaster response. In this paper, we propose a computational framework for harvesting local place names from geotagged housing advertisements. We make use of those advertisements posted on local-oriented websites, such as Craigslist, where local place names are often mentioned. The proposed framework consists of two stages: natural language processing (NLP) and geospatial clustering. The NLP stage examines the textual content of housing advertisements, and extracts place name candidates. The geospatial stage focuses on the coordinates associated with the extracted place name candidates, and performs multi-scale geospatial clustering to filter out the non-place names. We evaluate our framework by comparing its performance with those of six baselines. We also compare our result with four existing gazetteers to demonstrate the not-yet-recorded local place names discovered by our framework.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('14','tp_abstract')\">Close<\/a><\/p><\/div><\/div><\/div><h3 class=\"tp_h3\" id=\"tp_h3_2017\">2017<\/h3><div class=\"tp_publication tp_publication_article\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> Kessler, Carsten;  McKenzie, Grant<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('19','tp_links')\" style=\"cursor:pointer;\">A Geoprivacy Manifesto<\/a> <span class=\"tp_pub_type tp_  article\">Journal Article<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_in\">In: <\/span><span class=\"tp_pub_additional_journal\">Transactions in GIS, <\/span><span class=\"tp_pub_additional_volume\">vol. 22, <\/span><span class=\"tp_pub_additional_pages\">pp. 3-19, <\/span><span class=\"tp_pub_additional_year\">2017<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_19\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('19','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_19\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('19','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_19\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('19','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_19\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@article{40,<br \/>\r\ntitle = {A Geoprivacy Manifesto},<br \/>\r\nauthor = {Carsten Kessler and Grant McKenzie},<br \/>\r\nurl = {http:\/\/grantmckenzie.com\/academics\/GeoprivacyManifesto2017.pdf},<br \/>\r\ndoi = {10.1111\/tgis.12305},<br \/>\r\nyear  = {2017},<br \/>\r\ndate = {2017-12-01},<br \/>\r\njournal = {Transactions in GIS},<br \/>\r\nvolume = {22},<br \/>\r\npages = {3-19},<br \/>\r\nabstract = {As location-enabled technologies are becoming ubiquitous, our location is being shared with an ever-growing number of external services. Issues revolving around location privacy \u2013 or geoprivacy \u2013 therefore concern the vast majority of the population, largely without knowing how the underlying technologies work and what can be inferred from an individualtextquoterights location, especially if recorded over longer periods of time. Research, on the other hand, has largely treated this topic from isolated standpoints, most prominently from the technological and ethical point of view. This article therefore reflects upon the current state of geoprivacy from a broader perspective. It integrates technological, ethical, legal, and educational aspects and clarifies how they interact and shape how we deal with the corresponding technology, both individually and as a society. It does so in the form of a manifesto, consisting of 21 theses that summarize the main arguments made in the article. These theses argue that location information is different from other kinds of personal information and, in combination, show why geoprivacy (and privacy in general) needs to be protected and should not become a mere illusion. The fictional couple of Jane and Tom is used as a running example to illustrate how common it has become to share our location information, and how it can be used \u2013 both for good and for worse.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {article}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('19','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_19\" style=\"display:none;\"><div class=\"tp_abstract_entry\">As location-enabled technologies are becoming ubiquitous, our location is being shared with an ever-growing number of external services. Issues revolving around location privacy \u2013 or geoprivacy \u2013 therefore concern the vast majority of the population, largely without knowing how the underlying technologies work and what can be inferred from an individualtextquoterights location, especially if recorded over longer periods of time. Research, on the other hand, has largely treated this topic from isolated standpoints, most prominently from the technological and ethical point of view. This article therefore reflects upon the current state of geoprivacy from a broader perspective. It integrates technological, ethical, legal, and educational aspects and clarifies how they interact and shape how we deal with the corresponding technology, both individually and as a society. It does so in the form of a manifesto, consisting of 21 theses that summarize the main arguments made in the article. These theses argue that location information is different from other kinds of personal information and, in combination, show why geoprivacy (and privacy in general) needs to be protected and should not become a mere illusion. The fictional couple of Jane and Tom is used as a running example to illustrate how common it has become to share our location information, and how it can be used \u2013 both for good and for worse.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('19','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_19\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-file-pdf\"><\/i><a class=\"tp_pub_list\" href=\"http:\/\/grantmckenzie.com\/academics\/GeoprivacyManifesto2017.pdf\" title=\"http:\/\/grantmckenzie.com\/academics\/GeoprivacyManifesto2017.pdf\" target=\"_blank\">http:\/\/grantmckenzie.com\/academics\/GeoprivacyManifesto2017.pdf<\/a><\/li><li><i class=\"ai ai-doi\"><\/i><a class=\"tp_pub_list\" href=\"https:\/\/dx.doi.org\/10.1111\/tgis.12305\" title=\"Follow DOI:10.1111\/tgis.12305\" target=\"_blank\">doi:10.1111\/tgis.12305<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('19','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_conference\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> Janowicz, Krzysztof;  McKenzie, Grant<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('20','tp_links')\" style=\"cursor:pointer;\">How \"Alternative\" are Alternative Facts? Measuring Statement Coherence via Spatial Analysis<\/a> <span class=\"tp_pub_type tp_  conference\">Conference<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_booktitle\">25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2017), <\/span><span class=\"tp_pub_additional_organization\">ACM <\/span><span class=\"tp_pub_additional_publisher\">ACM, <\/span><span class=\"tp_pub_additional_address\">Redondo Beach, CA, USA, <\/span><span class=\"tp_pub_additional_year\">2017<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_20\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('20','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_20\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('20','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_20\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('20','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_20\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@conference{36,<br \/>\r\ntitle = {How \"Alternative\" are Alternative Facts? Measuring Statement Coherence via Spatial Analysis},<br \/>\r\nauthor = {Krzysztof Janowicz and Grant McKenzie},<br \/>\r\nurl = {http:\/\/grantmckenzie.com\/academics\/AlternativeFacts_ACM2017.pdf},<br \/>\r\nyear  = {2017},<br \/>\r\ndate = {2017-11-01},<br \/>\r\nbooktitle = {25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2017)},<br \/>\r\npublisher = {ACM},<br \/>\r\naddress = {Redondo Beach, CA, USA},<br \/>\r\norganization = {ACM},<br \/>\r\nabstract = {Following the AAA principle by which anybody can say anything about any topic, the Web is no stranger to alternative facts. Nonetheless, with the increasing volume and velocity at which content is being published and difficulties to assess the credibility of information and the trustworthiness of sources, alternative facts are becoming a major challenge and an instrument for spreading disinformation. Interestingly, the diversity of todaytextquoterights data sources can also help us to counter alternative facts by measuring their coherence, i.e., the degree to which data from one source confirms or contradict data from another source. While a single dataset can be biased towards supporting or discrediting a statement, the diverse sources of data across media types that are publicly accessible today offer unique perspectives on which to assess a given statement. To give an intuitive example, a statement about the comparison of crowd sizes should align with photos of said crowds. However, these photos could be taken at different times, from different viewpoints, and could lead to different, sample-based estimations. Adding further data from heterogeneous sources, such as metro ridership, can either further support a statement or contradict it. In this thought experiment we discuss the role of geographic data, knowledge graphs, and spatial analysis in approaching alternative facts from a novel angle, namely by studying their coherence, i.e., whether they align with other statements, instead of trying to falsify them. In doing so, we aim at increasing the costs for maintaining alternative facts.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {conference}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('20','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_20\" style=\"display:none;\"><div class=\"tp_abstract_entry\">Following the AAA principle by which anybody can say anything about any topic, the Web is no stranger to alternative facts. Nonetheless, with the increasing volume and velocity at which content is being published and difficulties to assess the credibility of information and the trustworthiness of sources, alternative facts are becoming a major challenge and an instrument for spreading disinformation. Interestingly, the diversity of todaytextquoterights data sources can also help us to counter alternative facts by measuring their coherence, i.e., the degree to which data from one source confirms or contradict data from another source. While a single dataset can be biased towards supporting or discrediting a statement, the diverse sources of data across media types that are publicly accessible today offer unique perspectives on which to assess a given statement. To give an intuitive example, a statement about the comparison of crowd sizes should align with photos of said crowds. However, these photos could be taken at different times, from different viewpoints, and could lead to different, sample-based estimations. Adding further data from heterogeneous sources, such as metro ridership, can either further support a statement or contradict it. In this thought experiment we discuss the role of geographic data, knowledge graphs, and spatial analysis in approaching alternative facts from a novel angle, namely by studying their coherence, i.e., whether they align with other statements, instead of trying to falsify them. In doing so, we aim at increasing the costs for maintaining alternative facts.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('20','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_20\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-file-pdf\"><\/i><a class=\"tp_pub_list\" href=\"http:\/\/grantmckenzie.com\/academics\/AlternativeFacts_ACM2017.pdf\" title=\"http:\/\/grantmckenzie.com\/academics\/AlternativeFacts_ACM2017.pdf\" target=\"_blank\">http:\/\/grantmckenzie.com\/academics\/AlternativeFacts_ACM2017.pdf<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('20','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_conference\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> McKenzie, Grant;  Adams, Benjamin<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('23','tp_links')\" style=\"cursor:pointer;\">Juxtaposing thematic regions derived from spatial and platial user-generated content.<\/a> <span class=\"tp_pub_type tp_  conference\">Conference<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_booktitle\">Proceedings of the 13th International Conference on Spatial Information Theory (COSIT textquoteright17), <\/span><span class=\"tp_pub_additional_organization\">Dagstuhl <\/span><span class=\"tp_pub_additional_publisher\">Dagstuhl, <\/span><span class=\"tp_pub_additional_address\">LtextquoterightAquila, Italy, <\/span><span class=\"tp_pub_additional_year\">2017<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_23\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('23','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_23\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('23','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_23\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('23','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_23\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@conference{37,<br \/>\r\ntitle = {Juxtaposing thematic regions derived from spatial and platial user-generated content.},<br \/>\r\nauthor = {Grant McKenzie and Benjamin Adams},<br \/>\r\nurl = {http:\/\/grantmckenzie.com\/academics\/ThematicRegions_2017.pdf},<br \/>\r\nyear  = {2017},<br \/>\r\ndate = {2017-09-01},<br \/>\r\nbooktitle = {Proceedings of the 13th International Conference on Spatial Information Theory (COSIT textquoteright17)},<br \/>\r\npublisher = {Dagstuhl},<br \/>\r\naddress = {LtextquoterightAquila, Italy},<br \/>\r\norganization = {Dagstuhl},<br \/>\r\nabstract = {Typical approaches to defining regions, districts or neighborhoods within a city often focus on place instances of a similar type that are grouped together. For example, most cities have at least one bar district defined as such by the clustering of bars within a few city blocks. In reality, it is not the presence of spatial locations labeled as bars that contribute to a bar region, but rather the popularity of the bars themselves. Following the principle that places, and by extension, placetype regions exist via the people that have given space meaning, we explore user-contributed content as a way of extracting this meaning. Kernel density estimation models of place-based social check-ins are compared to spatially tagged social posts with the goal of identifying thematic regions within the city of Los Angeles, CA. Dynamic human activity patterns, represented as temporal signatures, are included in this analysis to demonstrate how regions change over time.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {conference}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('23','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_23\" style=\"display:none;\"><div class=\"tp_abstract_entry\">Typical approaches to defining regions, districts or neighborhoods within a city often focus on place instances of a similar type that are grouped together. For example, most cities have at least one bar district defined as such by the clustering of bars within a few city blocks. In reality, it is not the presence of spatial locations labeled as bars that contribute to a bar region, but rather the popularity of the bars themselves. Following the principle that places, and by extension, placetype regions exist via the people that have given space meaning, we explore user-contributed content as a way of extracting this meaning. Kernel density estimation models of place-based social check-ins are compared to spatially tagged social posts with the goal of identifying thematic regions within the city of Los Angeles, CA. Dynamic human activity patterns, represented as temporal signatures, are included in this analysis to demonstrate how regions change over time.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('23','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_23\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-file-pdf\"><\/i><a class=\"tp_pub_list\" href=\"http:\/\/grantmckenzie.com\/academics\/ThematicRegions_2017.pdf\" title=\"http:\/\/grantmckenzie.com\/academics\/ThematicRegions_2017.pdf\" target=\"_blank\">http:\/\/grantmckenzie.com\/academics\/ThematicRegions_2017.pdf<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('23','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_conference\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> Lee, Myeong;  McKenzie, Grant;  Aghi, Rajat<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('18','tp_links')\" style=\"cursor:pointer;\">Exploratory cluster analysis of urban mobility patterns to identify neighborhood boundaries<\/a> <span class=\"tp_pub_type tp_  conference\">Conference<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_booktitle\">International Symposium on Location-Based Social Media Data and Tracking Data., <\/span><span class=\"tp_pub_additional_address\">Washington, D.C., <\/span><span class=\"tp_pub_additional_year\">2017<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_18\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('18','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_18\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('18','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_18\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('18','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_18\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@conference{52,<br \/>\r\ntitle = {Exploratory cluster analysis of urban mobility patterns to identify neighborhood boundaries},<br \/>\r\nauthor = {Myeong Lee and Grant McKenzie and Rajat Aghi},<br \/>\r\nurl = {http:\/\/www.grantmckenzie.com\/academics\/UrbanMobilityPatterns_2017.pdf},<br \/>\r\nyear  = {2017},<br \/>\r\ndate = {2017-07-01},<br \/>\r\nbooktitle = {International Symposium on Location-Based Social Media Data and Tracking Data.},<br \/>\r\naddress = {Washington, D.C.},<br \/>\r\nabstract = {Defining neighborhood boundaries within a city is a complex and often subjective task. Neighborhoods boundaries are defined by the people that visit and live in the region, and activities that occur within those boundaries. Depending on the individual or group activity being conducted, these boundaries can change substan- tially. Transportation and human mobility patterns offer a novel basis on which to explore and delineate neighborhoods. In this work we take a first, exploratory step in capturing dynamically changing neighborhoods based on two different types of urban mobility data. Through clustering temporal urban mobility signatures of alternative transportation users in Washington, D.C., this work provides implications about the characteristics of different types of mobility data and research directions.},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {conference}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('18','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_18\" style=\"display:none;\"><div class=\"tp_abstract_entry\">Defining neighborhood boundaries within a city is a complex and often subjective task. Neighborhoods boundaries are defined by the people that visit and live in the region, and activities that occur within those boundaries. Depending on the individual or group activity being conducted, these boundaries can change substan- tially. Transportation and human mobility patterns offer a novel basis on which to explore and delineate neighborhoods. In this work we take a first, exploratory step in capturing dynamically changing neighborhoods based on two different types of urban mobility data. Through clustering temporal urban mobility signatures of alternative transportation users in Washington, D.C., this work provides implications about the characteristics of different types of mobility data and research directions.<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('18','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_18\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-file-pdf\"><\/i><a class=\"tp_pub_list\" href=\"http:\/\/www.grantmckenzie.com\/academics\/UrbanMobilityPatterns_2017.pdf\" title=\"http:\/\/www.grantmckenzie.com\/academics\/UrbanMobilityPatterns_2017.pdf\" target=\"_blank\">http:\/\/www.grantmckenzie.com\/academics\/UrbanMobilityPatterns_2017.pdf<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('18','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><div class=\"tp_publication tp_publication_conference\"><div class=\"tp_pub_info\"><p class=\"tp_pub_author\"> McKenzie, Grant;  Janowicz, Krzysztof<\/p><p class=\"tp_pub_title\"><a class=\"tp_title_link\" onclick=\"teachpress_pub_showhide('17','tp_links')\" style=\"cursor:pointer;\">The Effect of Regional Variation and Resolution on Geosocial Thematic Signatures for Points of Interest<\/a> <span class=\"tp_pub_type tp_  conference\">Conference<\/span> <\/p><p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_booktitle\">Societal Geo-innovation. AGILE 2017, <\/span><span class=\"tp_pub_additional_organization\">Springer <\/span><span class=\"tp_pub_additional_publisher\">Springer, <\/span><span class=\"tp_pub_additional_address\">Wageningen, Netherlands, <\/span><span class=\"tp_pub_additional_year\">2017<\/span>.<\/p><p class=\"tp_pub_menu\"><span class=\"tp_abstract_link\"><a id=\"tp_abstract_sh_17\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('17','tp_abstract')\" title=\"Show abstract\" style=\"cursor:pointer;\">Abstract<\/a><\/span> | <span class=\"tp_resource_link\"><a id=\"tp_links_sh_17\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('17','tp_links')\" title=\"Show links and resources\" style=\"cursor:pointer;\">Links<\/a><\/span> | <span class=\"tp_bibtex_link\"><a id=\"tp_bibtex_sh_17\" class=\"tp_show\" onclick=\"teachpress_pub_showhide('17','tp_bibtex')\" title=\"Show BibTeX entry\" style=\"cursor:pointer;\">BibTeX<\/a><\/span><\/p><div class=\"tp_bibtex\" id=\"tp_bibtex_17\" style=\"display:none;\"><div class=\"tp_bibtex_entry\"><pre>@conference{38,<br \/>\r\ntitle = {The Effect of Regional Variation and Resolution on Geosocial Thematic Signatures for Points of Interest},<br \/>\r\nauthor = {Grant McKenzie and Krzysztof Janowicz},<br \/>\r\nurl = {http:\/\/grantmckenzie.com\/academics\/McKenzie_AGILE2017.pdf},<br \/>\r\nyear  = {2017},<br \/>\r\ndate = {2017-05-01},<br \/>\r\nbooktitle = {Societal Geo-innovation. AGILE 2017},<br \/>\r\npublisher = {Springer},<br \/>\r\naddress = {Wageningen, Netherlands},<br \/>\r\norganization = {Springer},<br \/>\r\nabstract = {Computational models of place are a key component of spatial information theory and play an increasing role in research ranging from spatial search to transportation studies. One method to arrive at such models is to extract knowledge from user-generated content e.g., from texts, tags, trajectories, pictures, and so forth. Over the last years, topic modeling techniques such as latent Dirichlet allocation (LDA) have been studied to reveal linguistic patterns that characterize places and their types. Intuitively, people are more likely to describe places such as Yosemite National Park in terms of hiking, nature, and camping than cocktail or dancing. The geo-indicativeness of non-georeferenced text does not only apply to place instances but also place types, e.g., state parks. While different parks will vary greatly with respect to their landscape and thus human descriptions, the distribution of topics common to all parks will differ significantly from other types of places, e.g., night clubs. This aggregation of topics to the type level creates thematic signatures that can be used for place categorization, data cleansing and conflation, semantic search, and so on. To make full use of these signatures, however, requires a better understanding of their intra-type variability as regional differences effect the predictive power of the signatures. Intuitively, the topic composition for place types such as store and office should be less effected by regional differences than the topic composition for types such as monument and mountain. In this work, we approach this regional variability hypothesis by attempting to prove that all place types are aspatial with respect to their thematic signatures. We reject this hypothesis by comparing the signature similarities of 316 place types between major cities in the U.S. We then select the most and least varying place types and compare them to thematic signatures from regions outside of the U.S. Finally, we explore the effects of LDA topic resolution on differences between and within place types},<br \/>\r\nkeywords = {},<br \/>\r\npubstate = {published},<br \/>\r\ntppubtype = {conference}<br \/>\r\n}<br \/>\r\n<\/pre><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('17','tp_bibtex')\">Close<\/a><\/p><\/div><div class=\"tp_abstract\" id=\"tp_abstract_17\" style=\"display:none;\"><div class=\"tp_abstract_entry\">Computational models of place are a key component of spatial information theory and play an increasing role in research ranging from spatial search to transportation studies. One method to arrive at such models is to extract knowledge from user-generated content e.g., from texts, tags, trajectories, pictures, and so forth. Over the last years, topic modeling techniques such as latent Dirichlet allocation (LDA) have been studied to reveal linguistic patterns that characterize places and their types. Intuitively, people are more likely to describe places such as Yosemite National Park in terms of hiking, nature, and camping than cocktail or dancing. The geo-indicativeness of non-georeferenced text does not only apply to place instances but also place types, e.g., state parks. While different parks will vary greatly with respect to their landscape and thus human descriptions, the distribution of topics common to all parks will differ significantly from other types of places, e.g., night clubs. This aggregation of topics to the type level creates thematic signatures that can be used for place categorization, data cleansing and conflation, semantic search, and so on. To make full use of these signatures, however, requires a better understanding of their intra-type variability as regional differences effect the predictive power of the signatures. Intuitively, the topic composition for place types such as store and office should be less effected by regional differences than the topic composition for types such as monument and mountain. In this work, we approach this regional variability hypothesis by attempting to prove that all place types are aspatial with respect to their thematic signatures. We reject this hypothesis by comparing the signature similarities of 316 place types between major cities in the U.S. We then select the most and least varying place types and compare them to thematic signatures from regions outside of the U.S. Finally, we explore the effects of LDA topic resolution on differences between and within place types<\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('17','tp_abstract')\">Close<\/a><\/p><\/div><div class=\"tp_links\" id=\"tp_links_17\" style=\"display:none;\"><div class=\"tp_links_entry\"><ul class=\"tp_pub_list\"><li><i class=\"fas fa-file-pdf\"><\/i><a class=\"tp_pub_list\" href=\"http:\/\/grantmckenzie.com\/academics\/McKenzie_AGILE2017.pdf\" title=\"http:\/\/grantmckenzie.com\/academics\/McKenzie_AGILE2017.pdf\" target=\"_blank\">http:\/\/grantmckenzie.com\/academics\/McKenzie_AGILE2017.pdf<\/a><\/li><\/ul><\/div><p class=\"tp_close_menu\"><a class=\"tp_close\" onclick=\"teachpress_pub_showhide('17','tp_links')\">Close<\/a><\/p><\/div><\/div><\/div><\/div><div class=\"tablenav\"><div class=\"tablenav-pages\"><span class=\"displaying-num\">68 entries<\/span> <a class=\"page-numbers button disabled\">&laquo;<\/a> <a class=\"page-numbers button disabled\">&lsaquo;<\/a> 1 of 2 <a href=\"https:\/\/platial.science\/pubs\/?limit=2&amp;tgid=&amp;yr=&amp;type=&amp;usr=&amp;auth=&amp;tsr=#tppubs\" title=\"next page\" class=\"page-numbers button\">&rsaquo;<\/a> <a href=\"https:\/\/platial.science\/pubs\/?limit=2&amp;tgid=&amp;yr=&amp;type=&amp;usr=&amp;auth=&amp;tsr=#tppubs\" title=\"last page\" class=\"page-numbers button\">&raquo;<\/a> <\/div><\/div><\/div>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":1,"featured_media":3703,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"twitterCardType":"","cardImageID":0,"cardImage":"","cardTitle":"","cardDesc":"","cardImageAlt":"","cardPlayer":"","cardPlayerWidth":0,"cardPlayerHeight":0,"cardPlayerStream":"","cardPlayerCodec":"","footnotes":""},"class_list":["post-3555","page","type-page","status-publish","has-post-thumbnail","hentry","post-has-thumbnail"],"_links":{"self":[{"href":"https:\/\/platial.science\/wp-json\/wp\/v2\/pages\/3555","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/platial.science\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/platial.science\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/platial.science\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/platial.science\/wp-json\/wp\/v2\/comments?post=3555"}],"version-history":[{"count":6,"href":"https:\/\/platial.science\/wp-json\/wp\/v2\/pages\/3555\/revisions"}],"predecessor-version":[{"id":3658,"href":"https:\/\/platial.science\/wp-json\/wp\/v2\/pages\/3555\/revisions\/3658"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/platial.science\/wp-json\/wp\/v2\/media\/3703"}],"wp:attachment":[{"href":"https:\/\/platial.science\/wp-json\/wp\/v2\/media?parent=3555"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}