Europe PMC

This website requires cookies, and the limited processing of your personal data in order to function. By using the site you are agreeing to this as outlined in our privacy notice and cookie policy.

Fast algorithm for detecting community structure in networks.

Author information

Affiliations

  • 1. Department of Physics and Center for the Study of Complex Systems, University of Michigan, Ann Arbor, Michigan 48109-1120, USA.
      Authors
    • Newman ME 1
    (1 author)

Physical review. E, Statistical, Nonlinear, and Soft Matter Physics, 18 Jun 2004, 69(6 Pt 2):066133
https://doi.org/10.1103/physreve.69.066133 PMID: 15244693 

Abstract 

Many networks display community structure--groups of vertices within which connections are dense but between which they are sparser--and sensitive computer algorithms have in recent years been developed for detecting this structure. These algorithms, however, are computationally demanding, which limits their application to small networks. Here we describe an 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 50,000 physicists.

Full text links 

Read article at publisher's site: https://doi.org/10.1103/physreve.69.066133

Read article for free, from open access legal sources, via Unpaywall: http://arxiv.org/pdf/cond-mat/0309508Unpaywall

References 

Articles referenced by this article (17)

Show 7 more references (10 of 17)

Citations & impact 

Impact metrics

508
Citations
Jump to Citations

Citations of article over time

Alternative metrics

Altmetric item for https://www.altmetric.com/details/3427759
Altmetric
Discover the attention surrounding your research
https://www.altmetric.com/details/3427759

Article citations

Go to all (508) article citations

Similar Articles 

To arrive at the top five similar articles we use a word-weighted algorithm to compare words from the Title and Abstract of each citation.