Extracting community structure through relational hypergraphs

Social media websites promote diverse user interaction on media objects as well as user actions with respect to other users. The goal of this work is to discover community structure in rich media social networks, and observe how it evolves over time, through analysis of multi-relational data. The problem is important in the enterprise domain where extracting emergent community structure on enterprise social media, can help in forming new collaborative teams, aid in expertise discovery, and guide long term enterprise reorganization. Our approach consists of three main parts: (1) a relational hypergraph model for modeling various social context and interactions; (2) a novel hypergraph factorization method for community extraction on multi-relational social data; (3) an online method to handle temporal evolution through incremental hypergraph factorization. Extensive experiments on real-world enterprise data suggest that our technique is scalable and can extract meaningful communities. T...

• Type: Conference
• Year: 2009
• Where: WWW
• Authors: Yu-Ru Lin, Jimeng Sun, Paul Castro, Ravi B. Konuru, Hari Sundaram, Aisling Kelliher
• Keywords: Enterprise Social Media, Hypergraph Factorization Method, Incremental Hypergraph Factorization, Internet Technology, WWW 2009