关键词: 社交网络, 社区发现, 话题模型, 用户影响力

Abstract: With the development of social network, users in all kinds of social networks form a large user graph. The articles published by users and the links between articles form a large document graph. According to the user graph and document graph, how to mine the topics, communities and user influence is an important problem, but now this problem is handled independently. Considering the inter-dependence of the problem and making use of text content and coauthor relationship, this paper proposes a joint model of topic modeling, community discovery and user influence analysis based on LDA (latent Dirichlet allocation), called ACT-LDA (author-community-topic LDA), which uses variation method for inference. The experiments on DBLP data show very good results, which validates the proposed model.

Key words: social network, community discovery, topic modeling, user influence