Papers by Adhimukti Prabhawa
E-BOOK, USE WISELY
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In recent years, social media has become ub... more E-BOOK, USE WISELY
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In recent years, social media has become ubiquitous and important for social networking and content sharing. And yet, the content that is generated from these websites remains largely untapped. In this paper, we demonstrate how social media content can be used to predict real-world outcomes. In particular, we use the chatter from Twitter.com to forecast box-office revenues for movies. We show that a simple model built from the rate at which tweets are created about particular topics can outperform market-based predictors. We further demonstrate how sentiments extracted from Twitter can be further utilized to improve the forecasting power of social media.
Merupakan sebuah teknik pembujuk rayuan secara persuasi untuk menghasilkan bujukan dengan melalui... more Merupakan sebuah teknik pembujuk rayuan secara persuasi untuk menghasilkan bujukan dengan melalui karakter pembicara, emosional, atau argumen. Retorika memainkan peranan yang sangat penting dalam setiap kegiatan bertutur karena retorik di satu pihak memberikan gambaran pemahaman yang lebih baik tentang manusia dalam hubungannya dengan kegiatan bertutur, sedangkan di pihak lain retorik membimbing orang membuat tuturnya lebih gambling, memikat, dan meyakinkan.
Books by Adhimukti Prabhawa
E-BOOK, USE WISELY
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While current literature has sufficiently pro... more E-BOOK, USE WISELY
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While current literature has sufficiently profiled word-of-mouth (WOM) marketing, customer relationship management, brand communities, search engine optimization, viral marketing, guerilla marketing, events-based marketing, and social media each on an isolated, individual basis, there is no comprehensive model that effectively incorporates all of these elements. The first purpose of this paper is to therefore profile the current literature landscape surrounding WOM marketing, alternative marketing communications, and social media as viable components of integrated marketing communications. Additionally, this paper aims to develop an integrated alternative marketing communication conceptual model that can be applied by industrial practitioners to help them achieve their marketing objectives.
E-BOOK, USE WISELY
----------------------------------
The quality of user-generated content varie... more E-BOOK, USE WISELY
----------------------------------
The quality of user-generated content varies drastically from excellent to abuse and spam. As the availability of such content increases, the task of identifying high-quality content in sites based on user contributions-social media sites-becomes increasingly important. Social media in general exhibit a rich variety of information sources: in addition to the content itself, there is a wide array of non-content information available, such as links between items and explicit quality ratings from members of the community. In this paper we investigate methods for exploiting such community feedback to automatically identify high quality content. As a test case, we focus on Yahoo! Answers, a large community question/answering portal that is particularly rich in the amount and types of content and social interactions available in it. We introduce a general classification framework for combining the evidence from different sources of information , that can be tuned automatically for a given social media type and quality definition. In particular, for the community question/answering domain, we show that our system is able to separate high-quality items from the rest with an accuracy close to that of humans.
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Papers by Adhimukti Prabhawa
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In recent years, social media has become ubiquitous and important for social networking and content sharing. And yet, the content that is generated from these websites remains largely untapped. In this paper, we demonstrate how social media content can be used to predict real-world outcomes. In particular, we use the chatter from Twitter.com to forecast box-office revenues for movies. We show that a simple model built from the rate at which tweets are created about particular topics can outperform market-based predictors. We further demonstrate how sentiments extracted from Twitter can be further utilized to improve the forecasting power of social media.
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This is the accepted version of the paper. This version of the publication may differ from the final published version. Permanent repository link: http://openaccess.city.ac.uk/5274/ Link to published version: http://dx.
Books by Adhimukti Prabhawa
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While current literature has sufficiently profiled word-of-mouth (WOM) marketing, customer relationship management, brand communities, search engine optimization, viral marketing, guerilla marketing, events-based marketing, and social media each on an isolated, individual basis, there is no comprehensive model that effectively incorporates all of these elements. The first purpose of this paper is to therefore profile the current literature landscape surrounding WOM marketing, alternative marketing communications, and social media as viable components of integrated marketing communications. Additionally, this paper aims to develop an integrated alternative marketing communication conceptual model that can be applied by industrial practitioners to help them achieve their marketing objectives.
----------------------------------
The quality of user-generated content varies drastically from excellent to abuse and spam. As the availability of such content increases, the task of identifying high-quality content in sites based on user contributions-social media sites-becomes increasingly important. Social media in general exhibit a rich variety of information sources: in addition to the content itself, there is a wide array of non-content information available, such as links between items and explicit quality ratings from members of the community. In this paper we investigate methods for exploiting such community feedback to automatically identify high quality content. As a test case, we focus on Yahoo! Answers, a large community question/answering portal that is particularly rich in the amount and types of content and social interactions available in it. We introduce a general classification framework for combining the evidence from different sources of information , that can be tuned automatically for a given social media type and quality definition. In particular, for the community question/answering domain, we show that our system is able to separate high-quality items from the rest with an accuracy close to that of humans.
----------------------------------
In recent years, social media has become ubiquitous and important for social networking and content sharing. And yet, the content that is generated from these websites remains largely untapped. In this paper, we demonstrate how social media content can be used to predict real-world outcomes. In particular, we use the chatter from Twitter.com to forecast box-office revenues for movies. We show that a simple model built from the rate at which tweets are created about particular topics can outperform market-based predictors. We further demonstrate how sentiments extracted from Twitter can be further utilized to improve the forecasting power of social media.
---------------------------------
This is the accepted version of the paper. This version of the publication may differ from the final published version. Permanent repository link: http://openaccess.city.ac.uk/5274/ Link to published version: http://dx.
--------------------------------
While current literature has sufficiently profiled word-of-mouth (WOM) marketing, customer relationship management, brand communities, search engine optimization, viral marketing, guerilla marketing, events-based marketing, and social media each on an isolated, individual basis, there is no comprehensive model that effectively incorporates all of these elements. The first purpose of this paper is to therefore profile the current literature landscape surrounding WOM marketing, alternative marketing communications, and social media as viable components of integrated marketing communications. Additionally, this paper aims to develop an integrated alternative marketing communication conceptual model that can be applied by industrial practitioners to help them achieve their marketing objectives.
----------------------------------
The quality of user-generated content varies drastically from excellent to abuse and spam. As the availability of such content increases, the task of identifying high-quality content in sites based on user contributions-social media sites-becomes increasingly important. Social media in general exhibit a rich variety of information sources: in addition to the content itself, there is a wide array of non-content information available, such as links between items and explicit quality ratings from members of the community. In this paper we investigate methods for exploiting such community feedback to automatically identify high quality content. As a test case, we focus on Yahoo! Answers, a large community question/answering portal that is particularly rich in the amount and types of content and social interactions available in it. We introduce a general classification framework for combining the evidence from different sources of information , that can be tuned automatically for a given social media type and quality definition. In particular, for the community question/answering domain, we show that our system is able to separate high-quality items from the rest with an accuracy close to that of humans.