%0 Conference Paper %1 Gir-02 %A Girvan, Michelle %A Newman, Mark E. J %D 2002 %J PNAS %K Biological Community Networks Social Structure and %T Community structure in social and biological networks %U http://www.pnas.org/cgi/content/full/99/12/7821 %X A number of recent studies have focused on the statistical properties of networked systems such as social networks and the Worldwide Web. Researchers have concentrated particularly on a few properties that seem to be common to many networks: the small-world property, power-law degree distributions, and network transitivity. In this article, we highlight another property that is found in many networks, the property of community structure, in which network nodes are joined together in tightly knit groups, between which there are only looser connections. We propose a method for detecting such communities, built around the idea of sing centrality indices to find community structure is already known and find that the the method detects this known structure with high sensitivity and reliability. We also apply the method to two networks whose community structure is not well known---a collaoration network and a food web---and find it detects significant and informative community divisions in both cases.

@inproceedings{Gir-02, abstract = {A number of recent studies have focused on the statistical properties of networked systems such as social networks and the Worldwide Web. Researchers have concentrated particularly on a few properties that seem to be common to many networks: the small-world property, power-law degree distributions, and network transitivity. In this article, we highlight another property that is found in many networks, the property of community structure, in which network nodes are joined together in tightly knit groups, between which there are only looser connections. We propose a method for detecting such communities, built around the idea of sing centrality indices to find community structure is already known and find that the the method detects this known structure with high sensitivity and reliability. We also apply the method to two networks whose community structure is not well known---a collaoration network and a food web---and find it detects significant and informative community divisions in both cases.}, added-at = {2008-03-13T16:33:57.000+0100}, author = {Girvan, Michelle and Newman, Mark E. J}, biburl = {https://www.bibsonomy.org/bibtex/21f8f1282da92501aa58cda919b9b28d5/bertil.hatt}, date-added = {2007-06-11 17:22:07 +0200}, date-modified = {2008-03-13 14:41:52 +0100}, description = {March 2008}, interhash = {ecd7a48a37f660ab421472140168c892}, intrahash = {1f8f1282da92501aa58cda919b9b28d5}, journal = {PNAS}, keywords = {Biological Community Networks Social Structure and}, rating = {0}, timestamp = {2008-03-13T16:34:04.000+0100}, title = {Community structure in social and biological networks}, uri = {papers://C3B117CD-23C4-4854-9426-AC96AFB113DA/Paper/p120}, url = {http://www.pnas.org/cgi/content/full/99/12/7821}, year = 2002 }