Vincent D Blondel et al J. Stat. Mech. (2008) P10008 doi:10.1088/1742-5468/2008/10/P10008
Vincent D Blondel1, Jean-Loup Guillaume1,2, Renaud Lambiotte1,3 and Etienne Lefebvre1
Show affiliationsWe propose a simple method to extract the community structure of large networks. Our method is a heuristic method that is based on modularity optimization. It is shown to outperform all other known community detection methods in terms of computation time. Moreover, the quality of the communities detected is very good, as measured by the so-called modularity. This is shown first by identifying language communities in a Belgian mobile phone network of 2 million customers and by analysing a web graph of 118 million nodes and more than one billion links. The accuracy of our algorithm is also verified on ad hoc modular networks.
E-print Number: 0803.0476
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89.75.Hc Networks and genealogical trees
89.65.Gh Economics; econophysics, financial markets, business and management
Issue 10 (October 2008)
Received 18 April 2008, accepted for publication 3 September 2008
Published 9 October 2008
Vincent D Blondel et al J. Stat. Mech. (2008) P10008
James P Bagrow J. Stat. Mech. (2008) P05001