It has been found that many networks display community structure -- groups of vertices within which connections are dense but between which they are sparser -- and highly sensitive computer algorithms have in recent years been developed for detecting such structure. These algorithms however are computationally demanding, which limits their application to small networks. Here we describe a new algorithm which gives excellent results when tested on both computer-generated and real-world networks and is much faster, typically thousands of times faster than previous algorithms. We give several example applications, including one to a collaboration network of more than 50000 physicists.
Beschreibung
Citebase - Fast algorithm for detecting community structure in networks
%0 Journal Article
%1 Newman03fastAlgorithm
%A Newman, M. E. J.
%D 2004
%J Physical Review E
%K Newman03fastAlgorithm clustering community discovery graph hierarchy
%P 066133
%T Fast algorithm for detecting community structure in networks
%U http://www.citebase.org/abstract?id=oai:arXiv.org:cond-mat/0309508
%V 69
%X It has been found that many networks display community structure -- groups of vertices within which connections are dense but between which they are sparser -- and highly sensitive computer algorithms have in recent years been developed for detecting such structure. These algorithms however are computationally demanding, which limits their application to small networks. Here we describe a new algorithm which gives excellent results when tested on both computer-generated and real-world networks and is much faster, typically thousands of times faster than previous algorithms. We give several example applications, including one to a collaboration network of more than 50000 physicists.
@article{Newman03fastAlgorithm,
abstract = {It has been found that many networks display community structure -- groups of vertices within which connections are dense but between which they are sparser -- and highly sensitive computer algorithms have in recent years been developed for detecting such structure. These algorithms however are computationally demanding, which limits their application to small networks. Here we describe a new algorithm which gives excellent results when tested on both computer-generated and real-world networks and is much faster, typically thousands of times faster than previous algorithms. We give several example applications, including one to a collaboration network of more than 50000 physicists.},
added-at = {2008-10-29T18:25:14.000+0100},
author = {Newman, M. E. J.},
biburl = {https://www.bibsonomy.org/bibtex/2f208740efaa81e40420855f88a0a5649/lee_peck},
description = {Citebase - Fast algorithm for detecting community structure in networks},
interhash = {1590c30798300a013ca3792aab93ee48},
intrahash = {f208740efaa81e40420855f88a0a5649},
journal = {Physical Review E},
keywords = {Newman03fastAlgorithm clustering community discovery graph hierarchy},
pages = 066133,
timestamp = {2008-10-29T18:25:14.000+0100},
title = {Fast algorithm for detecting community structure in networks},
url = {http://www.citebase.org/abstract?id=oai:arXiv.org:cond-mat/0309508},
volume = 69,
year = 2004
}