Sentiment community detection in social networks

Authors:
Kaiquan Xu;Jiexun Li;Stephen Shaoyi Liao
Affiliations:
City University of Hong Kong, Hong Kong;Drexel University, Philadelphia, PA;City University of Hong Kong, Hong Kong
Venue:
Proceedings of the 2011 iConference
Year:
2011

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Abstract

With the increasing popularity of social networking sites and Web 2.0, people are building social relationships and expressing their opinions in the cyberspace. In this study, we introduce several novel methods to identify online communities with similar sentiments in online social networks. Our preliminary experiment on a real-world dataset demonstrates that our proposed method can detect interesting sentiment communities in social networks.