{ "id": "cond-mat/0308217", "version": "v1", "published": "2003-08-11T21:21:03.000Z", "updated": "2003-08-11T21:21:03.000Z", "title": "Finding and evaluating community structure in networks", "authors": [ "M. E. J. Newman", "M. Girvan" ], "comment": "16 pages, 13 figures", "journal": "Phys. Rev. E 69, 026113 (2004)", "doi": "10.1103/PhysRevE.69.026113", "categories": [ "cond-mat.stat-mech", "cond-mat.dis-nn" ], "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.", "revisions": [ { "version": "v1", "updated": "2003-08-11T21:21:03.000Z" } ], "analyses": { "subjects": [ "89.75.Hc", "87.23.Ge", "89.20.Hh", "05.10.-a" ], "keywords": [ "evaluating community structure", "discovering community structure", "algorithms", "real-world network data", "network nodes" ], "tags": [ "journal article", "famous paper" ], "publication": { "publisher": "APS", "journal": "Physical Review E", "year": 2004, "month": "Feb", "volume": 69, "number": 2, "pages": "026113" }, "note": { "typesetting": "TeX", "pages": 16, "language": "en", "license": "arXiv", "status": "editable", "adsabs": "2004PhRvE..69b6113N" } } }