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.Comment: The free academic research software, CFinder, used for the
publication is available at the website of the publication:
http://www.cfinder.or
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