Wednesday, February 10,  2010 - 3:30 p.m. - Noyce

Community Detection Algorithms:  A Comparative Analysis

Santo Fortunato, Institute for Scientific Interchange (ISI), Italy

Uncovering the community structure exhibited by real networks is a crucial step towards an understanding of complex systems that goes beyond the local organization of their constituents. Many algorithms have been proposed so far, but none of them has been subjected to strict tests to evaluate their performance. Here we test several methods against a recently introduced class of realistic benchmark graphs, with heterogeneous distributions of degree and community size. The methods are also tested against the benchmark by Girvan and Newman and on random graphs. As a result of our analysis, three recent algorithms introduced by Rosvall and Bergstrom, Blondel et al. and Ronhovde and Nussinov, respectively, have an excellent performance, with the additional advantage of low computational complexity, which enables one to analyze large systems.

SFI Host: Luis Bettencourt

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