Sentiment community detection in social networks
Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
| Original language | English |
|---|---|
| Title of host publication | ACM International Conference Proceeding Series |
| Pages | 804-805 |
| Publication status | Published - 2011 |
Conference
| Title | 6th Annual Conference on 2011 iConference: Inspiration, Integrity, and Intrepidity, iConference 2011 |
|---|---|
| Place | United States |
| City | Seattle, WA |
| Period | 8 - 11 February 2011 |
Link(s)
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. Copyright © 2011 ACM.
Research Area(s)
- Community detection, Sentiment analysis, Social networks
Citation Format(s)
Sentiment community detection in social networks. / Xu, Kaiquan; Li, Jiexun; Liao, Stephen Shaoyi.
ACM International Conference Proceeding Series. 2011. p. 804-805.
ACM International Conference Proceeding Series. 2011. p. 804-805.
Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review
