Towards Community Discovery in Signed Collaborative Interaction Networks

Abstract--We propose a framework for discovery of collaborative community structure in Wiki-based knowledge repositories based on raw-content generation analysis. We leverage topic modelling in order to capture agreement and opposition of contributors and analyze these multi-modal relations to map communities in the contributor base. The key steps of our approach include (i) modeling of pairwise variable-strength contributor interactions that can be both positive and negative, (ii) synthesis of a global network incorporating all pairwise interactions, and (iii) detection and analysis of community structure encoded in such networks. The global community discovery algorithm we propose outperforms existing alternatives in identifying coherent clusters according to objective optimality criteria. Analysis of the discovered community structure reveals coalitions of commoninterest editors who back each other in promoting some topics and collectively oppose other coalitions or single authors. ...

• Type: Journal
• Year: 2010
• Where: ICDM
• Authors: Petko Bogdanov, Nicholas D. Larusso, Ambuj K. Singh
• Keywords: Community Structure, Contributor Interactions, Data Mining, ICDM 2010, Variable-strength Contributor Interactions