MetaFac: community discovery via relational hypergraph factorization
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Situation detection and control using spatio-temporal analysis of microblogs
Proceedings of the 19th international conference on World wide web
Who says what to whom on twitter
Proceedings of the 20th international conference on World wide web
Probabilistic factor models for web site recommendation
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
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In micro-blogging, people talk about their daily life and change minds freely, thus by mining people's interest in micro-blogging, we will easily perceive the pulse of society. In this paper, we catch what people are caring about in their daily life by discovering meaningful communities based on probabilistic factor model (PFM). The proposed solution identifies people's interest from their friendship and content information. Therefore, it reveals the behaviors of people in micro-blogging naturally. Experimental results verify the effectiveness of the proposed model and show people's social life vividly.