Title: Communities detection and the analysis of their dynamics in collaborative networks
Authors: Celine Robardet, Eric Fleury
Addresses: Universite de Lyon, CNRS INSA-Lyon, LIRIS, UMR 5205, F-69621, France. ' Universite de Lyon, ENS Lyon, INRIA/A4RES, ENS Lyon – 69364 Lyon Cedex 07, France
Abstract: The analysis of graphs like collaborative networks aims at studying the relationships between individuals, instead of individual attributes or properties. One of the interesting substructures of such a graph is a community structure, which is a subset of nodes that are more densely linked when compared with the rest of the network. Such dense subgraphs gather individuals who share similar interests depending on the type of relation encoded in the graph. In this paper we tackle the problem of identifying communities in dynamic networks. We propose an approach based on the random walk to identify communities in evolving graphs like collaborative networks. We apply this approach to the Infocom co-authorship network to determine stable collaborations and evolving communities. We use such information, combined with other Digital Bibliography & Library Project (DBLP) co-authorship network topology features, to analyse the formation of the programme committee board of a conference.
Keywords: social network analysis; community identification; dynamic graph analysis; information diffusion; collaborative networks; co-authorship analysis; dynamic networks; web based communities; random walk.
DOI: 10.1504/IJWBC.2009.023965
International Journal of Web Based Communities, 2009 Vol.5 No.2, pp.195 - 211
Published online: 22 Mar 2009 *
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