Community detection in directed acyclic graphs

Leo Speidel, Taro Takaguchi, Naoki Masuda*

*この研究の対応する著者

研究成果: Article査読

13 被引用数 (Scopus)

抄録

Some temporal networks, most notably citation networks, are naturally represented as directed acyclic graphs (DAGs). To detect communities in DAGs, we propose a modularity for DAGs by defining an appropriate null model (i.e., randomized network) respecting the order of nodes. We implement a spectral method to approximately maximize the proposed modularity measure and test the method on citation networks and other DAGs. We find that the attained values of the modularity for DAGs are similar for partitions that we obtain by maximizing the proposed modularity (designed for DAGs), the modularity for undirected networks and that for general directed networks. In other words, if we neglect the order imposed on nodes (and the direction of links) in a given DAG and maximize the conventional modularity measure, the obtained partition is close to the optimal one in the sense of the modularity for DAGs.

本文言語English
論文番号203
ジャーナルEuropean Physical Journal B
88
8
DOI
出版ステータスPublished - 2015 8 10
外部発表はい

ASJC Scopus subject areas

  • 電子材料、光学材料、および磁性材料
  • 凝縮系物理学

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