Finding and evaluating community structure in networks

Details Finding and evaluating community structure in networks Finding and evaluating community structure in networks

2003-08-11

arxiv.org/abs/cond-mat/0308217v1

Phys. Rev. E 69, 026113 (2004)

Physics

Condensed Matter

Statistical Mechanics

16 pages, 13 figures

Scientific paper

10.1103/PhysRevE.69.026113

We propose and study a set of algorithms for discovering community structure in networks -- natural divisions of network nodes into densely connected subgroups. Our algorithms all share two definitive features: first, they involve iterative removal of edges from the network to split it into communities, the edges removed being identified using one of a number of possible "betweenness" measures, and second, these measures are, crucially, recalculated after each removal. We also propose a measure for the strength of the community structure found by our algorithms, which gives us an objective metric for choosing the number of communities into which a network should be divided. We demonstrate that our algorithms are highly effective at discovering community structure in both computer-generated and real-world network data, and show how they can be used to shed light on the sometimes dauntingly complex structure of networked systems.

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