Applying to Twitter Networks of a Community Extraction Method Using Intersection Graph and Semantic Analysis

  • Toshiya Kuramochi
  • Naoki Okada
  • Kyohei Tanikawa
  • Yoshinori Hijikata
  • Shogo Nishida
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8006)


Many researchers have studied about complex networks such as the World Wide Web, social networks and the protein interaction network. One hot topic in this area is community detection. For example, in the WWW, the community shows a set of web pages about a certain topic. The community structure is unquestionably a key characteristic of complex networks. We have proposed the novel community extracting method. The method considers the overlaps between communities using the idea of the intersection graph. Additionally, we address the problem of edge inhomogeneity by weiting edges using content information. Finally, we conduct clustering based on modularity. In this paper, we evaluate our method through applying to real microblog networks.


complex network community extraction intersection graph hierarchical clustering text mining microblog network 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Toshiya Kuramochi
    • 1
  • Naoki Okada
    • 1
  • Kyohei Tanikawa
    • 1
  • Yoshinori Hijikata
    • 1
  • Shogo Nishida
    • 1
  1. 1.Graduate School of Engineering ScienceOsaka UniversityToyonakaJapan

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