%0 Generic %1 Newman2003Finding %A Newman, M. E. J. %A Girvan, M. %D 2003 %K algorithm, betweenness, centrality %T Finding and evaluating community structure in networks %U http://arxiv.org/abs/cond-mat/0308217 %X 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.

@misc{Newman2003Finding, abstract = {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.}, added-at = {2009-09-24T14:55:30.000+0200}, archiveprefix = {arXiv}, author = {Newman, M. E. J. and Girvan, M.}, biburl = {https://www.bibsonomy.org/bibtex/21bd36e98dd5877a404b1742e56d446ed/andreacapocci}, citeulike-article-id = {154}, citeulike-linkout-0 = {http://arxiv.org/abs/cond-mat/0308217}, citeulike-linkout-1 = {http://arxiv.org/pdf/cond-mat/0308217}, eprint = {cond-mat/0308217}, interhash = {7892b08fd9c96782d075e92787ce3323}, intrahash = {1bd36e98dd5877a404b1742e56d446ed}, keywords = {algorithm, betweenness, centrality}, month = {August}, posted-at = {2007-09-15 21:31:44}, priority = {5}, timestamp = {2009-09-24T14:55:35.000+0200}, title = {Finding and evaluating community structure in networks}, url = {http://arxiv.org/abs/cond-mat/0308217}, year = 2003 }