Community detection in complex networks using extremal optimization

We propose a method to find the community structure in complex networks based on an extremal optimization of the value of modularity. The method outperforms the optimal modularity found by the existing algorithms in the literature giving a better understanding of the community structure. We present...

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Bibliographic Details
Published in:Physical review. E, Statistical, nonlinear, and soft matter physics Statistical, nonlinear, and soft matter physics, 2005-08, Vol.72 (2 Pt 2), p.027104-027104, Article 027104
Main Authors: Duch, Jordi, Arenas, Alex
Format: Article
Language:English
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Summary:We propose a method to find the community structure in complex networks based on an extremal optimization of the value of modularity. The method outperforms the optimal modularity found by the existing algorithms in the literature giving a better understanding of the community structure. We present the results of the algorithm for computer-simulated and real networks and compare them with other approaches. The efficiency and accuracy of the method make it feasible to be used for the accurate identification of community structure in large complex networks.
ISSN:1539-3755
1550-2376
DOI:10.1103/physreve.72.027104