Community structure in directed networks

by: EA Leicht, MEJ Newman

(27 Sep 2007)

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arXiv (abstract), arXiv (PDF)

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Abstract

We consider the problem of finding communities or modules in directed networks. The most common approach to this problem in the previous literature has been simply to ignore edge direction and apply methods developed for community discovery in undirected networks, but this approach discards potentially useful information contained in the edge directions. Here we show how the widely used benefit function known as modularity can be generalized in a principled fashion to incorporate the information contained in edge directions. This in turn allows us to find communities by maximizing the modularity over possible divisions of a network, which we do using an algorithm based on the eigenvectors of the corresponding modularity matrix. This method is shown to give demonstrably better results than previous methods on a variety of test networks, both real and computer-generated.

@misc{citeulike:1837596, abstract = {We consider the problem of finding communities or modules in directed networks. The most common approach to this problem in the previous literature has been simply to ignore edge direction and apply methods developed for community discovery in undirected networks, but this approach discards potentially useful information contained in the edge directions. Here we show how the widely used benefit function known as modularity can be generalized in a principled fashion to incorporate the information contained in edge directions. This in turn allows us to find communities by maximizing the modularity over possible divisions of a network, which we do using an algorithm based on the eigenvectors of the corresponding modularity matrix. This method is shown to give demonstrably better results than previous methods on a variety of test networks, both real and computer-generated.}, author = {Leicht, E. A. and Newman, M. E. J. }, citeulike-article-id = {1837596}, eprint = {0709.4500}, keywords = {community, directed, network}, month = {Sep}, posted-at = {2008-06-23 05:42:00}, priority = {2}, title = {Community structure in directed networks}, url = {http://arxiv.org/abs/0709.4500}, year = {2007} }

RIS record

TY - ELEC ID - citeulike:1837596 L3 - citeulike-article-id:1837596 N2 - We consider the problem of finding communities or modules in directed networks. The most common approach to this problem in the previous literature has been simply to ignore edge direction and apply methods developed for community discovery in undirected networks, but this approach discards potentially useful information contained in the edge directions. Here we show how the widely used benefit function known as modularity can be generalized in a principled fashion to incorporate the information contained in edge directions. This in turn allows us to find communities by maximizing the modularity over possible divisions of a network, which we do using an algorithm based on the eigenvectors of the corresponding modularity matrix. This method is shown to give demonstrably better results than previous methods on a variety of test networks, both real and computer-generated. TI - Community structure in directed networks KW - community KW - directed KW - network AU - Leicht, EA AU - Newman, MEJ PY - 2007/Sep/27/ UR - http://arxiv.org/abs/0709.4500 ER -

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