Abstract
Social media such as Web forum often have dense interactions between user and content where network models are often appropriate for analysis. Joint non-negative matrix factorization model of participation and content data can be viewed as a bipartite graph model between users and media and is proposed for analysis social media. The factorizations allow simultaneous automatic discovery of leaders and sub-communities in the Web forum as well as the core latent topics in the forum. Results on topic detection of Web forums and cluster analysis show that social features are highly effective for forum analvsis.
| Original language | English |
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| Title of host publication | WWW '08: Proceedings of the 17th international conference on World Wide Web |
| Editors | Jinpeng Huai, Robin Chen, Hsiao-Wuen Hon, Yunhao Liu |
| Place of Publication | New York |
| Publisher | Association for Computing Machinery (ACM) |
| Pages | 1245-1246 |
| Number of pages | 2 |
| ISBN (Print) | 9781605580852 |
| DOIs | |
| Publication status | Published - 21 Apr 2008 |
| Event | 17th International Conference on World Wide Web, WWW 2008 - Beijing, China Duration: 21 Apr 2008 → 25 Apr 2008 https://dl.acm.org/doi/proceedings/10.1145/1367497 |
Publication series
| Name | Proceeding of the 17th International Conference on World Wide Web 2008, WWW'08 |
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Conference
| Conference | 17th International Conference on World Wide Web, WWW 2008 |
|---|---|
| Country/Territory | China |
| City | Beijing |
| Period | 21/04/08 → 25/04/08 |
| Internet address |
Scopus Subject Areas
- Computer Networks and Communications
User-Defined Keywords
- Latent inter-est detection
- Latent topic detection
- Social Network Analysis