文章基本信息

标题：A Community Finding Method for Weighted Dynamic Online Social Network Based on User Behavior
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作者：Dongming Chen ; Yanlin Dong ; Xinyu Huang 等
期刊名称：International Journal of Distributed Sensor Networks
印刷版ISSN：1550-1329
电子版ISSN：1550-1477
出版年度：2015
卷号：2015
DOI：10.1155/2015/306160
出版社：Hindawi Publishing Corporation
摘要：Revealing the structural features of social networks is vitally important to both scientific research and practice, and the explosive growth of online social networks in recent years has brought us dramatic advances to understand social structures. Here we proposed a community detection approach based on user interaction behavior in weighted dynamic online social networks. We researched interaction behaviors in online social networks and built a directed and unweighted network model in terms of the Weibo following relationships between social individuals at the very beginning. In order to refine the interaction behavior, level one fuzzy comprehensive evaluation model was employed to describe how closely individuals are connected to each other. According to this intimate degree description, weights are tagged to the prior unweighted model we built. Secondly, a heuristic community detection algorithm for dynamic network was provided based on the improved version of modularity called module density. As for the heuristic rule, we chose greedy strategy and merely fed the algorithms with the changed parts within neighboring time slice. Experimental results show that the proposed algorithm can obtain high accuracy and simultaneously get comparatively lower time complexity than some typical algorithms. More importantly, our algorithm needs no a priori conditions.