To facilitate users' ability to make sense of large collections of hypertext we present two n... more To facilitate users' ability to make sense of large collections of hypertext we present two new techniques for inducing clusters of related documents on the World Wide Web. Users' ability to find relevant information might also be enhanced by finding lawful properties of document behavior and use. We present models and analyses of document use and change for the World Wide Web. URI http://hdl.handle.net/1853/3532 Collections GVU Center Technical Reports [542] About ļ Terms of Use ļ Contact Us Emergency Information ļ Legal & Privacy Information ļ Accessibility ļ Accountability ļ Accreditation ļ Employment ļ Life, Death, and Lawfullness on the Electronic Frontier ī
COGLE (COmmon Ground Learning and Explanation) is an explainable artificial intelligence (XAI) sy... more COGLE (COmmon Ground Learning and Explanation) is an explainable artificial intelligence (XAI) system where autonomous drones deliver supplies to field units in mountainous areas. The mission risks vary with topography, flight decisions, and mission goals. The missions engage a human plus AI team where users determine which of two AIācontrolled drones is better for each mission. This article reports on the technical approach and findings of the project and reflects on challenges that complex combinatorial problems present for users, machine learning, user studies, and the context of use for XAI systems. COGLE creates explanations in multiple modalities. Narrative āWhatā explanations compare what each drone does on a mission and āWhyā based on drone competencies determined from experiments using counterfactuals. Visual āWhereā explanations highlight risks on maps to help users to interpret flight plans. One branch of the research studied whether the explanations helped users to predi...
Journal of the Association for Information Science and Technology, 2015
Deciding whether a claim is true or false often requires a deeper understanding of the evidence s... more Deciding whether a claim is true or false often requires a deeper understanding of the evidence supporting and contradicting the claim. However, when presented with many evidence documents, users do not necessarily read and trust them uniformly. Psychologists and other researchers have shown that users tend to follow and agree with articles and sources that hold viewpoints similar to their own, a phenomenon known as confirmation bias. This suggests that when learning about a controversial topic, human biases and viewpoints about the topic may affect what is considered ātrustworthyā or credible. It is an interesting challenge to build systems that can help users overcome this bias and help them decide the truthfulness of claims. In this article, we study various factors that enable humans to acquire additional information about controversial claims in an unbiased fashion. Specifically, we designed a user study to understand how presenting evidence with contrasting viewpoints and sour...
Novel methods of promoting self-monitoring and social support are needed to ensure long-term main... more Novel methods of promoting self-monitoring and social support are needed to ensure long-term maintenance of behavior change. In this paper, we directly investigate the effects of group support in an exercise and nutrition program delivered by an mHealth application called Fittle. Our first specific study aim was to explore whether social support improved adherence in wellness programs. Our second specific study aim was to assess whether media types (ePaper vs mobile) were associated with different levels of compliance and adherence to wellness programs. The third aim was to assess whether the use of an mHealth application led to positive changes to participants' eating behavior, physical activity, and stress level, compared to traditional paper-based programs. A 2 Ć 2 (eg, Media: Mobile vs ePaper Ć Group Type: Team vs Solo) factorial design feasibility study was conducted. A sample of 124 volunteers who were interested in improving eating behavior, increasing physical activity, ...
Surfing the World Wide Web (WWW) involves traversing hyperlink connections among documents. The a... more Surfing the World Wide Web (WWW) involves traversing hyperlink connections among documents. The ability to predict surfing patterns could solve many problems facing producers and consumers of WWW content. We analyzed WWW server logs for a WWW site, collected over ten days, to compare different path reconstruction methods and to investigate how past surfing behavior predicts future surfing choices. Since log files do not explicitly contain user paths, various methods have evolved to reconstruct user paths. Session times, number of clicks per visit, and Levenshtein Distance analyses were performed to show the impact of various reconstruction methods. Different methods for measuring surfing patterns were also compared. Markov model approximations were used to model the probability of users choosing links conditional on past surfing paths. Information-theoretic (entropy) measurements suggest that information is gained by using longer paths to estimate the conditional probability of link choice given surf path. The improvements diminish, however, as one increases the length of path beyond one. Information-theoretic (total divergence to the average entropy) measurements suggest that the conditional probabilities of link choice given surf path are more stable over time for shorter paths than longer paths. Direct examination of the accuracy of the conditional probability models in predicting test data also suggests that shorter paths yield more stable models and can be estimated reliably with less data than longer paths.
In this paper, we propose an ACT-R cognitive model for making credibility judgments about the cre... more In this paper, we propose an ACT-R cognitive model for making credibility judgments about the credibility of Twitter authors. We abstracted the cognitive processes involved in three levels: attending to information on Web page, comprehending information to identify credibility cues, and integrating credibility cues to make a judgment. We represent basic knowledge required for credibility judgment using declarative memory in ACT-R that is seeded with experiences of Twitter messages that have been passed through a Latent Dirichlet Allocation topic modeling process. Comparisons of model credibility judgments to human credibility judgments from controlled experiments show weak to strong correlations that range from r = 0.32 to r = 0.75 depending on the specific task.
In this paper, we summarized recent work in modeling how users socially forage and search for inf... more In this paper, we summarized recent work in modeling how users socially forage and search for information. One way to bridge between different communities of users is to diversify their information sources. This can be done using not only old mechanisms such as email, instant messages, newsgroups and bulletin boards, but also new ones such as wikis, blogs, social tags, etc. How do users work with diverse hints from other foragers? How do interference effects change their strategies? How can we build tools that help users cooperatively search? We seek theories that might help us answer these questions, or at least point us toward the right directions.
Proceedings of the SIGCHI conference on Human factors in computing systems common ground - CHI '96, 1996
In its current implementation, the WorldWide Web lacks much of the explicit structure and strong ... more In its current implementation, the WorldWide Web lacks much of the explicit structure and strong typing found in many closed hypertext systems. While this property probably relates to the explosive acceptance of the Web, it further complicates the already difficult problem of identifying usable structures and aggregates in large hypertext collections. These reduced structures, or localities, form the basis for simplifying visualizations of and navigation through complex hypertext systems. Much of the previous research into identifying aggregates utilize graph theoretic algorithms based upon structural topology, i.e., the linkages between items. Other research has focused on content analysis to form document collections. This paper presents our exploration into techniques that utilize both the topology and textual similarity between items as well as usage data collected by servers and page meta-information lke title and size. Linear equations and spreading activation models are employed to arrange Web pages based upon functional categories, node types, and relevancy.
CHI '01 Extended Abstracts on Human Factors in Computing Systems, 2001
In this paper, we present three taxonomic classification schemes based on Web users' responses to... more In this paper, we present three taxonomic classification schemes based on Web users' responses to what Web activities significantly impacted their decisions and actions. The taxonomic classifications focus on three variables: the Purpose of people's search on the Web, the Method people use to find information, and the Content of the information for which they are searching. These taxonomies are useful for understanding people's activity on the Web and for developing ecologically-valid tasks to be used when studying Web behavior.
Proceedings of the 21st ACM international conference on Information and knowledge management, 2012
Deciding whether a claim is true or false often requires understanding the evidence supporting an... more Deciding whether a claim is true or false often requires understanding the evidence supporting and contradicting the claim. However, when learning about a controversial claim, human biases and viewpoints may affect which evidence documents are considered "trustworthy" or credible. It is important to overcome this bias and know both viewpoints to get a balanced perspective. In this paper, we study various factors that affect learning about the truthfulness of controversial claims. We designed a user study to understand the impact of these factors. Specifically, we studied the impact of presenting evidence with contrasting viewpoints and source expertise rating on how users accessed the evidence documents. This would help us optimize how to teach users about controversial topics in the most effective way, and to design better claim verification systems. We find that users do not seek contrasting viewpoints by themselves, but explicitly presenting contrasting evidence helps them get a well-rounded understanding of the topic. Furthermore, explicit knowledge of the source credibility and the context not only affects what users read, but also how credible they perceive the document to be.
Intelligence analysts engage in information seeking, evaluation, prediction, and reporting behavi... more Intelligence analysts engage in information seeking, evaluation, prediction, and reporting behavior in an extremely information-intensive work environment. A Cognitive Task Analysis (CTA) was conducted on intelligence analysts to capture data that will provide input to support development of a computational model of the analyst's processes and analytic strategies. A hybrid method was used to conduct the CTA, including a modified version of the critical decision method. Participants were asked to describe an example of a critical analysis assignment where they had to collect, analyze, and produce a report on intelligence of a strategic nature. Procedures used to conduct the CTA are described in this chapter along with initial results. Several factors contribute to making the analyst's task challenging: (i) time pressure, (ii) a high cognitive workload, and (iii) difficult human judgments. Human judgments are involved in considering the plausibility of information, deciding what information to trust, and determining how much weight to place on specific pieces of data. Intelligence analysis involves a complex process of assessing the reliability of information from a wide variety of sources and combining seemingly unrelated events. This problem is challenging because it involves aspects of data mining, data correlation and human judgment.
Proceedings of the SIGCHI conference on Human factors in computing systems - CHI '98, 1998
Designers and researchers of human-computer interaction need tools that permit the rapid explorat... more Designers and researchers of human-computer interaction need tools that permit the rapid exploration aa management of hypotheses about complex interactions of designs, task conditions, and user strategies. Dynamic programming is introduced as a such a tool for the analysis of information foraging technologies. The technique is illustrated in the context of the Scatter/Gather text clustering browser. Hypothetical improvements in browser speed ma text clustering are examined in the context of variations in task deadlines and the quality of the document repository. A complex and non-intuitive set of tradeof% emerge from even this simple space of factors, illustrating the general utility ofthe approach. Keywords Dynamic programming, SoatterEather, user models. information foraging Permission to make digit&hard copies ofall or pat ofthii material for personal or classroom use is granted witbout fee provided that the copies arenotmade or diiiuted for profit or commercial advantage, the copyright notice, the title ofthe publication and its date appear, and notice is. given that copyright is by permission of the ACM, Inc. To copy otherwise. to republish, to post on servers or to redistribute to lists requires specific permission and/or fee CHl 9s Los Angeles CA USA Copyright 199s 0-~9791-975-0/9s/4..s5.00
Proceedings of the ACM SIGCHI Conference on Human factors in computing systems, 1997
To facilitate users' ability to make sense of large collections of hypertext we present two new t... more To facilitate users' ability to make sense of large collections of hypertext we present two new techniques for inducing clusters of related documents on the World Wide Web. Users' ability to find relevant information might also be enhanced by finding lawful properties of document behavior and use. We present models and analyses of document use and change for the World Wide Web.
In this paper, we propose an ACT-R cognitive model for making credibility judgments about the cre... more In this paper, we propose an ACT-R cognitive model for making credibility judgments about the credibility of Twitter authors. We abstracted the cognitive processes involved in three levels: attending to information on Web page, comprehending information to identify credibility cues, and integrating credibility cues to make a judgment. We represent basic knowledge required for making credibility judgment using declarative memory in ACT-R which is seeded with experiences of Twitter messages that have been passed through a Latent Dirichlet Allocation topic modeling process. Comparisons of model credibility judgments to human credibility judgments from controlled experiments show weak to strong correlations that range from r = 0.31 to r = 0.83 depending on the specific task.
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 2009
User interfaces and information systems have become increasingly social in recent years, aimed at... more User interfaces and information systems have become increasingly social in recent years, aimed at supporting the decentralized, cooperative production and use of content. A theory that predicts the impact of interface and interaction designs on such factors as participation rates and knowledge discovery is likely to be useful. This paper reviews a variety of observed phenomena in social information foraging and sketches a framework extending Information Foraging Theory towards making predictions about the effects of diversity, interference, and cost-ofeffort on performance time, participation rates, and utility of discoveries.
Neuromodulatory systems and prefrontal cortex are involved in a number of decision-making context... more Neuromodulatory systems and prefrontal cortex are involved in a number of decision-making contexts. In this work, we adapt a recent neural network model that simulates interactions between neuromodulatory and prefrontal areas to the problem of prognostic foraging-that is choosing information to update or form a hypothesis. In the context of a simulated geospatial intelligence task, the model assesses a number of decision variables and strategies to choose actions that maximize information utility to more accurately predict the actions of an adversary. The model is also capable of modeling biases in decision making such as deviations from the optimal solution of maximizing information gain. Comparisons to other approaches and problem domains in information foraging are also discussed.
CHI '14 Extended Abstracts on Human Factors in Computing Systems, 2014
Over the past 30 years science has played a key role in shaping and advancing research in Human-C... more Over the past 30 years science has played a key role in shaping and advancing research in Human-Computer Interaction. Informed in part by methods, theories and findings from the behavioral sciences and from computer science, scientific contributions to HCI have provided explanations of how and why people interact through and with technology. We argue that the contribution of science to HCI could be enhanced if key challenges are met. During a SIG meeting we will discuss the challenges and potential responses and set an agenda for the coming years.
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 2009
We developed a low-effort interaction method called Click2Tag for social bookmarking. Information... more We developed a low-effort interaction method called Click2Tag for social bookmarking. Information foraging theory predicts that the production of tags will increase as the effort required to do so is lowered, while the amount of time invested decreases. However, models of human memory suggest that changes in the tagging process may affect subsequent human memory for the tagged material. We compared (1) low-effort tagging by mouse-clicking (Click2Tag), (2) traditional tagging by typing (type-to-tag), and (3) baseline, no tagging conditions. Our results suggest that (a) Click2Tag increases tagging rates, (b) Click2Tag improves recognition of facts from the tagged text when compared to type-to-tag, and (c) Click2Tag is comparable to the no-tagging baseline condition on recall measures. Results suggest that tagging by clicking strengthens the memory traces by repeated readings of relevant words in the text and, thus, improves recognition.
To facilitate users' ability to make sense of large collections of hypertext we present two n... more To facilitate users' ability to make sense of large collections of hypertext we present two new techniques for inducing clusters of related documents on the World Wide Web. Users' ability to find relevant information might also be enhanced by finding lawful properties of document behavior and use. We present models and analyses of document use and change for the World Wide Web. URI http://hdl.handle.net/1853/3532 Collections GVU Center Technical Reports [542] About ļ Terms of Use ļ Contact Us Emergency Information ļ Legal & Privacy Information ļ Accessibility ļ Accountability ļ Accreditation ļ Employment ļ Life, Death, and Lawfullness on the Electronic Frontier ī
COGLE (COmmon Ground Learning and Explanation) is an explainable artificial intelligence (XAI) sy... more COGLE (COmmon Ground Learning and Explanation) is an explainable artificial intelligence (XAI) system where autonomous drones deliver supplies to field units in mountainous areas. The mission risks vary with topography, flight decisions, and mission goals. The missions engage a human plus AI team where users determine which of two AIācontrolled drones is better for each mission. This article reports on the technical approach and findings of the project and reflects on challenges that complex combinatorial problems present for users, machine learning, user studies, and the context of use for XAI systems. COGLE creates explanations in multiple modalities. Narrative āWhatā explanations compare what each drone does on a mission and āWhyā based on drone competencies determined from experiments using counterfactuals. Visual āWhereā explanations highlight risks on maps to help users to interpret flight plans. One branch of the research studied whether the explanations helped users to predi...
Journal of the Association for Information Science and Technology, 2015
Deciding whether a claim is true or false often requires a deeper understanding of the evidence s... more Deciding whether a claim is true or false often requires a deeper understanding of the evidence supporting and contradicting the claim. However, when presented with many evidence documents, users do not necessarily read and trust them uniformly. Psychologists and other researchers have shown that users tend to follow and agree with articles and sources that hold viewpoints similar to their own, a phenomenon known as confirmation bias. This suggests that when learning about a controversial topic, human biases and viewpoints about the topic may affect what is considered ātrustworthyā or credible. It is an interesting challenge to build systems that can help users overcome this bias and help them decide the truthfulness of claims. In this article, we study various factors that enable humans to acquire additional information about controversial claims in an unbiased fashion. Specifically, we designed a user study to understand how presenting evidence with contrasting viewpoints and sour...
Novel methods of promoting self-monitoring and social support are needed to ensure long-term main... more Novel methods of promoting self-monitoring and social support are needed to ensure long-term maintenance of behavior change. In this paper, we directly investigate the effects of group support in an exercise and nutrition program delivered by an mHealth application called Fittle. Our first specific study aim was to explore whether social support improved adherence in wellness programs. Our second specific study aim was to assess whether media types (ePaper vs mobile) were associated with different levels of compliance and adherence to wellness programs. The third aim was to assess whether the use of an mHealth application led to positive changes to participants' eating behavior, physical activity, and stress level, compared to traditional paper-based programs. A 2 Ć 2 (eg, Media: Mobile vs ePaper Ć Group Type: Team vs Solo) factorial design feasibility study was conducted. A sample of 124 volunteers who were interested in improving eating behavior, increasing physical activity, ...
Surfing the World Wide Web (WWW) involves traversing hyperlink connections among documents. The a... more Surfing the World Wide Web (WWW) involves traversing hyperlink connections among documents. The ability to predict surfing patterns could solve many problems facing producers and consumers of WWW content. We analyzed WWW server logs for a WWW site, collected over ten days, to compare different path reconstruction methods and to investigate how past surfing behavior predicts future surfing choices. Since log files do not explicitly contain user paths, various methods have evolved to reconstruct user paths. Session times, number of clicks per visit, and Levenshtein Distance analyses were performed to show the impact of various reconstruction methods. Different methods for measuring surfing patterns were also compared. Markov model approximations were used to model the probability of users choosing links conditional on past surfing paths. Information-theoretic (entropy) measurements suggest that information is gained by using longer paths to estimate the conditional probability of link choice given surf path. The improvements diminish, however, as one increases the length of path beyond one. Information-theoretic (total divergence to the average entropy) measurements suggest that the conditional probabilities of link choice given surf path are more stable over time for shorter paths than longer paths. Direct examination of the accuracy of the conditional probability models in predicting test data also suggests that shorter paths yield more stable models and can be estimated reliably with less data than longer paths.
In this paper, we propose an ACT-R cognitive model for making credibility judgments about the cre... more In this paper, we propose an ACT-R cognitive model for making credibility judgments about the credibility of Twitter authors. We abstracted the cognitive processes involved in three levels: attending to information on Web page, comprehending information to identify credibility cues, and integrating credibility cues to make a judgment. We represent basic knowledge required for credibility judgment using declarative memory in ACT-R that is seeded with experiences of Twitter messages that have been passed through a Latent Dirichlet Allocation topic modeling process. Comparisons of model credibility judgments to human credibility judgments from controlled experiments show weak to strong correlations that range from r = 0.32 to r = 0.75 depending on the specific task.
In this paper, we summarized recent work in modeling how users socially forage and search for inf... more In this paper, we summarized recent work in modeling how users socially forage and search for information. One way to bridge between different communities of users is to diversify their information sources. This can be done using not only old mechanisms such as email, instant messages, newsgroups and bulletin boards, but also new ones such as wikis, blogs, social tags, etc. How do users work with diverse hints from other foragers? How do interference effects change their strategies? How can we build tools that help users cooperatively search? We seek theories that might help us answer these questions, or at least point us toward the right directions.
Proceedings of the SIGCHI conference on Human factors in computing systems common ground - CHI '96, 1996
In its current implementation, the WorldWide Web lacks much of the explicit structure and strong ... more In its current implementation, the WorldWide Web lacks much of the explicit structure and strong typing found in many closed hypertext systems. While this property probably relates to the explosive acceptance of the Web, it further complicates the already difficult problem of identifying usable structures and aggregates in large hypertext collections. These reduced structures, or localities, form the basis for simplifying visualizations of and navigation through complex hypertext systems. Much of the previous research into identifying aggregates utilize graph theoretic algorithms based upon structural topology, i.e., the linkages between items. Other research has focused on content analysis to form document collections. This paper presents our exploration into techniques that utilize both the topology and textual similarity between items as well as usage data collected by servers and page meta-information lke title and size. Linear equations and spreading activation models are employed to arrange Web pages based upon functional categories, node types, and relevancy.
CHI '01 Extended Abstracts on Human Factors in Computing Systems, 2001
In this paper, we present three taxonomic classification schemes based on Web users' responses to... more In this paper, we present three taxonomic classification schemes based on Web users' responses to what Web activities significantly impacted their decisions and actions. The taxonomic classifications focus on three variables: the Purpose of people's search on the Web, the Method people use to find information, and the Content of the information for which they are searching. These taxonomies are useful for understanding people's activity on the Web and for developing ecologically-valid tasks to be used when studying Web behavior.
Proceedings of the 21st ACM international conference on Information and knowledge management, 2012
Deciding whether a claim is true or false often requires understanding the evidence supporting an... more Deciding whether a claim is true or false often requires understanding the evidence supporting and contradicting the claim. However, when learning about a controversial claim, human biases and viewpoints may affect which evidence documents are considered "trustworthy" or credible. It is important to overcome this bias and know both viewpoints to get a balanced perspective. In this paper, we study various factors that affect learning about the truthfulness of controversial claims. We designed a user study to understand the impact of these factors. Specifically, we studied the impact of presenting evidence with contrasting viewpoints and source expertise rating on how users accessed the evidence documents. This would help us optimize how to teach users about controversial topics in the most effective way, and to design better claim verification systems. We find that users do not seek contrasting viewpoints by themselves, but explicitly presenting contrasting evidence helps them get a well-rounded understanding of the topic. Furthermore, explicit knowledge of the source credibility and the context not only affects what users read, but also how credible they perceive the document to be.
Intelligence analysts engage in information seeking, evaluation, prediction, and reporting behavi... more Intelligence analysts engage in information seeking, evaluation, prediction, and reporting behavior in an extremely information-intensive work environment. A Cognitive Task Analysis (CTA) was conducted on intelligence analysts to capture data that will provide input to support development of a computational model of the analyst's processes and analytic strategies. A hybrid method was used to conduct the CTA, including a modified version of the critical decision method. Participants were asked to describe an example of a critical analysis assignment where they had to collect, analyze, and produce a report on intelligence of a strategic nature. Procedures used to conduct the CTA are described in this chapter along with initial results. Several factors contribute to making the analyst's task challenging: (i) time pressure, (ii) a high cognitive workload, and (iii) difficult human judgments. Human judgments are involved in considering the plausibility of information, deciding what information to trust, and determining how much weight to place on specific pieces of data. Intelligence analysis involves a complex process of assessing the reliability of information from a wide variety of sources and combining seemingly unrelated events. This problem is challenging because it involves aspects of data mining, data correlation and human judgment.
Proceedings of the SIGCHI conference on Human factors in computing systems - CHI '98, 1998
Designers and researchers of human-computer interaction need tools that permit the rapid explorat... more Designers and researchers of human-computer interaction need tools that permit the rapid exploration aa management of hypotheses about complex interactions of designs, task conditions, and user strategies. Dynamic programming is introduced as a such a tool for the analysis of information foraging technologies. The technique is illustrated in the context of the Scatter/Gather text clustering browser. Hypothetical improvements in browser speed ma text clustering are examined in the context of variations in task deadlines and the quality of the document repository. A complex and non-intuitive set of tradeof% emerge from even this simple space of factors, illustrating the general utility ofthe approach. Keywords Dynamic programming, SoatterEather, user models. information foraging Permission to make digit&hard copies ofall or pat ofthii material for personal or classroom use is granted witbout fee provided that the copies arenotmade or diiiuted for profit or commercial advantage, the copyright notice, the title ofthe publication and its date appear, and notice is. given that copyright is by permission of the ACM, Inc. To copy otherwise. to republish, to post on servers or to redistribute to lists requires specific permission and/or fee CHl 9s Los Angeles CA USA Copyright 199s 0-~9791-975-0/9s/4..s5.00
Proceedings of the ACM SIGCHI Conference on Human factors in computing systems, 1997
To facilitate users' ability to make sense of large collections of hypertext we present two new t... more To facilitate users' ability to make sense of large collections of hypertext we present two new techniques for inducing clusters of related documents on the World Wide Web. Users' ability to find relevant information might also be enhanced by finding lawful properties of document behavior and use. We present models and analyses of document use and change for the World Wide Web.
In this paper, we propose an ACT-R cognitive model for making credibility judgments about the cre... more In this paper, we propose an ACT-R cognitive model for making credibility judgments about the credibility of Twitter authors. We abstracted the cognitive processes involved in three levels: attending to information on Web page, comprehending information to identify credibility cues, and integrating credibility cues to make a judgment. We represent basic knowledge required for making credibility judgment using declarative memory in ACT-R which is seeded with experiences of Twitter messages that have been passed through a Latent Dirichlet Allocation topic modeling process. Comparisons of model credibility judgments to human credibility judgments from controlled experiments show weak to strong correlations that range from r = 0.31 to r = 0.83 depending on the specific task.
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 2009
User interfaces and information systems have become increasingly social in recent years, aimed at... more User interfaces and information systems have become increasingly social in recent years, aimed at supporting the decentralized, cooperative production and use of content. A theory that predicts the impact of interface and interaction designs on such factors as participation rates and knowledge discovery is likely to be useful. This paper reviews a variety of observed phenomena in social information foraging and sketches a framework extending Information Foraging Theory towards making predictions about the effects of diversity, interference, and cost-ofeffort on performance time, participation rates, and utility of discoveries.
Neuromodulatory systems and prefrontal cortex are involved in a number of decision-making context... more Neuromodulatory systems and prefrontal cortex are involved in a number of decision-making contexts. In this work, we adapt a recent neural network model that simulates interactions between neuromodulatory and prefrontal areas to the problem of prognostic foraging-that is choosing information to update or form a hypothesis. In the context of a simulated geospatial intelligence task, the model assesses a number of decision variables and strategies to choose actions that maximize information utility to more accurately predict the actions of an adversary. The model is also capable of modeling biases in decision making such as deviations from the optimal solution of maximizing information gain. Comparisons to other approaches and problem domains in information foraging are also discussed.
CHI '14 Extended Abstracts on Human Factors in Computing Systems, 2014
Over the past 30 years science has played a key role in shaping and advancing research in Human-C... more Over the past 30 years science has played a key role in shaping and advancing research in Human-Computer Interaction. Informed in part by methods, theories and findings from the behavioral sciences and from computer science, scientific contributions to HCI have provided explanations of how and why people interact through and with technology. We argue that the contribution of science to HCI could be enhanced if key challenges are met. During a SIG meeting we will discuss the challenges and potential responses and set an agenda for the coming years.
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 2009
We developed a low-effort interaction method called Click2Tag for social bookmarking. Information... more We developed a low-effort interaction method called Click2Tag for social bookmarking. Information foraging theory predicts that the production of tags will increase as the effort required to do so is lowered, while the amount of time invested decreases. However, models of human memory suggest that changes in the tagging process may affect subsequent human memory for the tagged material. We compared (1) low-effort tagging by mouse-clicking (Click2Tag), (2) traditional tagging by typing (type-to-tag), and (3) baseline, no tagging conditions. Our results suggest that (a) Click2Tag increases tagging rates, (b) Click2Tag improves recognition of facts from the tagged text when compared to type-to-tag, and (c) Click2Tag is comparable to the no-tagging baseline condition on recall measures. Results suggest that tagging by clicking strengthens the memory traces by repeated readings of relevant words in the text and, thus, improves recognition.
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Papers by Peter Pirolli