Topic Detection in Online Discussion Using Non-negative Matrix Factorization
WI-IATW '07 Proceedings of the 2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops
Online Discussion Participation Prediction Using Non-negative Matrix Factorization
WI-IATW '07 Proceedings of the 2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops
Online Communities: A Social Computing Perspective
PAISI, PACCF and SOCO '08 Proceedings of the IEEE ISI 2008 PAISI, PACCF, and SOCO international workshops on Intelligence and Security Informatics
Hot Topic Detection on BBS Using Aging Theory
WISM '09 Proceedings of the International Conference on Web Information Systems and Mining
Mobile social closeness and communication patterns
CCNC'10 Proceedings of the 7th IEEE conference on Consumer communications and networking conference
Topic-based social network analysis for virtual communities of interests in the Dark Web
ACM SIGKDD Workshop on Intelligence and Security Informatics
Topic-based social network analysis for virtual communities of interests in the dark web
ACM SIGKDD Explorations Newsletter
Agent-based modeling of netizen groups in chinese internet events
PAISI'11 Proceedings of the 6th Pacific Asia conference on Intelligence and security informatics
Leveraging Social Network Analysis with Topic Models and the Semantic Web
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 03
Building a role search engine for social media
Proceedings of the 21st international conference companion on World Wide Web
Ontology paper: Community analysis through semantic rules and role composition derivation
Web Semantics: Science, Services and Agents on the World Wide Web
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Leveraging social network analysis with topic models and the Semantic Web extended
Web Intelligence and Agent Systems - Web Intelligence and Communities
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As more and more people join online communities, the ability to better understand membersý roles becomes critical to preserving and improving the health of those communities. We propose a novel approach to identifying key members and their roles by discovering implicit knowledge from online communities. Viewing an online community as a social network connected by poster-poster relationships, the approach takes advantage of the strengths of social network analysis and weighting schemes from information retrieval in identifying key members. Experimental studies were carried out to empirically evaluate the proposed approach with real-world data collected from a Usenet bulletin board over a one year period. The results showed that the proposed approach can not only identify prominent members whose behaviors are community supportive but also filter chatters whose behaviors are superficial to the online community. The findings have broad implications for online communities by allowing moderators to better support their members and by enabling members to better understand the conversation space.