Centrality properties of directed module members in social networks

Péter Pollner, Gergely Palla, Dániel Ábel, András Vicsek, Illés J. Farkas, Imre Derényi, Tamás Vicsek

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

Several recent studies of complex networks have suggested algorithms for locating network communities, also called modules or clusters, which are mostly defined as groups of nodes with dense internal connections. Along with the rapid development of these clustering techniques, the ability of revealing overlaps between communities has become very important as well. An efficient search technique for locating overlapping modules is provided by the Clique Percolation Method (CPM) and its extension to directed graphs, the CPMd algorithm. Here we investigate the centrality properties of directed module members in social networks obtained from e-mail exchanges and from sociometric questionnaires. Our results indicate that nodes in the overlaps between modules play a central role in the studied systems. Furthermore, the two different types of networks show interesting differences in the relation between the centrality measures and the role of the nodes in the directed modules.

Original languageEnglish
Pages (from-to)4959-4966
Number of pages8
JournalPhysica A: Statistical Mechanics and its Applications
Volume387
Issue number19-20
DOIs
Publication statusPublished - Aug 1 2008

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Keywords

  • Clustering
  • Community finding
  • Directed networks
  • Network modules
  • Overlapping modules

ASJC Scopus subject areas

  • Statistics and Probability
  • Condensed Matter Physics

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