Social and semantics analysis via non-negative matrix factorization

Zhi-li Wu, Chi-wa Cheng, Chun-hung Li

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

4 Citations (Scopus)

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 languageEnglish
Title of host publicationWWW '08: Proceedings of the 17th international conference on World Wide Web
EditorsJinpeng Huai, Robin Chen, Hsiao-Wuen Hon, Yunhao Liu
Place of PublicationNew York
PublisherAssociation for Computing Machinery (ACM)
Pages1245-1246
Number of pages2
ISBN (Print)9781605580852
DOIs
Publication statusPublished - 21 Apr 2008
Event17th International Conference on World Wide Web, WWW 2008 - Beijing, China
Duration: 21 Apr 200825 Apr 2008
https://dl.acm.org/doi/proceedings/10.1145/1367497

Conference

Conference17th International Conference on World Wide Web, WWW 2008
Country/TerritoryChina
CityBeijing
Period21/04/0825/04/08
Internet address

Scopus Subject Areas

  • Computer Networks and Communications

User-Defined Keywords

  • Latent inter-est detection
  • Latent topic detection
  • Social Network Analysis

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