Finding and evaluating community structure in networks
摘要
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.
引用
@article{arxiv.cond-mat/0308217,
title = {Finding and evaluating community structure in networks},
author = {M. E. J. Newman and M. Girvan},
journal= {arXiv preprint arXiv:cond-mat/0308217},
year = {2009}
}
备注
16 pages, 13 figures