关键词: 复杂网络, 社团结构发现, 信息传播, 多关系社交网络, 多子网复合复杂网络模型

Abstract: There are many relationships among users of social networks. These relationships determine the division of user??s community structure in a network. To detect community structure in multiple relationships social networks accurately, a community detection algorithm in multiple relationships social networks based on the study of information propagation process in multi-subnet composited complex network model is proposed. According to information propagation in the multiple relationships social network, the nodes in the network can be transformed into vector which can be suitable for clustering algorithm, and then clustering algorithm can be used to detect community structure in multiple relationships social networks. The algorithm takes the interaction of multiple relationships in the network and the interaction between heterogeneous nodes into consideration, and generates the information matrix which can represent the influence of each node on the entire network. The nodes with similar influence would be divided into the same community structure finally. The experiment results show that, compared with the traditional community structure detection algorithm, the proposed algorithm can not only improve the accuracy, but also divide heterogeneous nodes into a community to mine hidden information in multi-relationship social network according to different needs of users.

Key words: complex network, community detection, information propagation, multiple relationships online social network, multi-subnet composited complex network