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文章基本信息

  • 标题:Topic-oriented community detection of rating-based social networks
  • 作者:Ali Reihanian ; Behrouz Minaei-Bidgoli ; Hosein Alizadeh
  • 期刊名称:Journal of King Saud University @?C Computer and Information Sciences
  • 印刷版ISSN:1319-1578
  • 出版年度:2016
  • 卷号:28
  • 期号:3
  • 页码:303-310
  • DOI:10.1016/j.jksuci.2015.07.001
  • 出版社:Elsevier
  • 摘要:Nowadays, real world social networks contain a vast range of information including shared objects, comments, following information, etc. Finding meaningful communities in this kind of networks is an interesting research area and has attracted the attention of many researchers. The community structure of complex networks reveals both their organization and hidden relations among their constituents. Most of the researches in the field of community detection mainly focus on the topological structure of the network without performing any content analysis. In recent years, a number of researches have proposed approaches which consider both the contents that are interchanged in networks, and the topological structures of the networks in order to find more meaningful communities. In this research, the effect of topic analysis in finding more meaningful communities in social networking sites in which the users express their feelings toward different objects (like movies) by means of rating is demonstrated by performing extensive experiments.
  • 关键词:Content analysis ; Topical community ; Community detection ; Modularity ; Purity
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