Computer Science ›› 2017, Vol. 44 ›› Issue (7): 197-202.doi: 10.11896/j.issn.1002-137X.2017.07.035

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Community Detection Based on User Interaction and Link Analysis in Social Networks

LI Peng, LI Ying-le, WANG Kai, HE Zan-yuan, LI Xing and CHANG Zhen-chao   

  • Online:2018-11-13 Published:2018-11-13

Abstract: With the rapid development of social media network,the user is also more convenient to participate in social networking,which also brings a large number of complex interaction and connection mode.How to effectively analysis the interactive information and the connection information between network nodes to complete the efficient community detection is the key problem faced by current network analysis.Based on this,this paper put forward a kind of social network community detection method(CDUILS) based on the interaction behavior and link analysis.In this method,the interaction information between nodes is used as the cooperative learning of the community.The non negative matrix factorization is used to analyze the two types of information sources by the way of iterative update,and the community results can be obtained with two kinds of information retrieval.Experiments on real data sets show that the proposed method can effectively utilize the interaction behavior to guide the community division and have better quality of community division.

Key words: Interaction information,Non-negative matrix factorization,Social network,Community detection

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