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Full-Text Articles in Physical Sciences and Mathematics
Anomaly Detection Through Enhanced Sentiment Analysis On Social Media Data, Zhaoxia Wang, Victor Joo, Chuan Tong, Xin Xin, Hoong Chor Chin
Anomaly Detection Through Enhanced Sentiment Analysis On Social Media Data, Zhaoxia Wang, Victor Joo, Chuan Tong, Xin Xin, Hoong Chor Chin
Research Collection School Of Computing and Information Systems
Anomaly detection in sentiment analysis refers to detecting abnormal opinions, sentiment patterns or special temporal aspects of such patterns in a collection of data. The anomalies detected may be due to sudden sentiment changes hidden in large amounts of text. If these anomalies are undetected or poorly managed, the consequences may be severe, e.g. A business whose customers reveal negative sentiments and will no longer support the establishment. Social media platforms, such as Twitter, provide a vast source of information, which includes user feedback, opinion and information on most issues. Many organizations also leverage social media platforms to publish information …
Issues Of Social Data Analytics With A New Method For Sentiment Analysis Of Social Media Data, Zhaoxia Wang, Victor J. C. Tong, David Chan
Issues Of Social Data Analytics With A New Method For Sentiment Analysis Of Social Media Data, Zhaoxia Wang, Victor J. C. Tong, David Chan
Research Collection School of Social Sciences
Social media data consists of feedback, critiques and other comments that are posted online by internet users. Collectively, these comments may reflect sentiments that are sometimes not captured in traditional data collection methods such as administering a survey questionnaire. Thus, social media data offers a rich source of information, which can be adequately analyzed and understood. In this paper, we survey the extant research literature on sentiment analysis and discuss various limitations of the existing analytical methods. A major limitation in the large majority of existing research is the exclusive focus on social media data in the English language. There …
On Joint Modeling Of Topical Communities And Personal Interest In Microblogs, Tuan-Anh Hoang, Ee Peng Lim
On Joint Modeling Of Topical Communities And Personal Interest In Microblogs, Tuan-Anh Hoang, Ee Peng Lim
Research Collection School Of Computing and Information Systems
In this paper, we propose the Topical Communities and Personal Interest (TCPI) model for simultaneously modeling topics, topical communities, and users’ topical interests in microblogging data. TCPI considers different topical communities while differentiating users’ personal topical interests from those of topical communities, and learning the dependence of each user on the affiliated communities to generate content. This makes TCPI different from existing models that either do not consider the existence of multiple topical communities, or do not differentiate between personal and community’s topical interests. Our experiments on two Twitter datasets show that TCPI can effectively mine the representative topics for …
Partisan Sharing: Facebook Evidence And Societal Consequences, Jisun An, Daniele Quercia, Jon Crowcroft
Partisan Sharing: Facebook Evidence And Societal Consequences, Jisun An, Daniele Quercia, Jon Crowcroft
Research Collection School Of Computing and Information Systems
The hypothesis of selective exposure assumes that people seek out information that supports their views and eschew information that conflicts with their beliefs, and that has negative consequences on our society. Few researchers have recently found counter evidence of selective exposure in social media: users are exposed to politically diverse articles. No work has looked at what happens after exposure, particularly how individuals react to such exposure, though. Users might well be exposed to diverse articles but share only the partisan ones. To test this, we study partisan sharing on Facebook: the tendency for users to predominantly share like-minded news …
Sharing Political News: The Balancing Act Of Intimacy And Socialization In Selective Exposure, Jisun An, Daniele Quercia, Meeyoung Cha, Krishna Gummadi, Jon Crowcroft
Sharing Political News: The Balancing Act Of Intimacy And Socialization In Selective Exposure, Jisun An, Daniele Quercia, Meeyoung Cha, Krishna Gummadi, Jon Crowcroft
Research Collection School Of Computing and Information Systems
One might think that, compared to traditional media, social media sites allow people to choose more freely what to read and what to share, especially for politically oriented news. However, reading and sharing habits originate from deeply ingrained behaviors that might be hard to change. To test the extent to which this is true, we propose a Political News Sharing (PoNS) model that holistically captures four key aspects of social psychology: gratification, selective exposure, socialization, and trust & intimacy. Using real instances of political news sharing in Twitter, we study the predictive power of these features. As one might expect, …
Opinion Mining Of Sociopolitical Comments From Social Media, Swapna Gottipati
Opinion Mining Of Sociopolitical Comments From Social Media, Swapna Gottipati
Dissertations and Theses Collection (Open Access)
Opinions are central to almost all human activities by influencing greatly the decision making process. In this thesis, we present the problems of mining issues, extracting entities and suggestive opinions towards the entities, detecting thoughtful comments, and extracting stances and ideological expressions from online comments in the sociopolitical domain. This study is essential for opinion mining applications that are beneficial for policy makers, government sectors and social organizations. Much work has been done to try to uncover consumer sentiments from online comments to help businesses improve their products and services. However, sociopolitical opinion mining poses new challenges due to complex …