Applying to twitter networks of a community extraction method using intersection graph and semantic analysis

Authors:
Toshiya Kuramochi;Naoki Okada;Kyohei Tanikawa;Yoshinori Hijikata;Shogo Nishida
Affiliations:
Graduate School of Engineering Science, Osaka University, Toyonaka, Osaka, Japan;Graduate School of Engineering Science, Osaka University, Toyonaka, Osaka, Japan;Graduate School of Engineering Science, Osaka University, Toyonaka, Osaka, Japan;Graduate School of Engineering Science, Osaka University, Toyonaka, Osaka, Japan;Graduate School of Engineering Science, Osaka University, Toyonaka, Osaka, Japan
Venue:
HCI'13 Proceedings of the 15th international conference on Human-Computer Interaction: users and contexts of use - Volume Part III
Year:
2013

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Abstract

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.