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.

Keywords

Computer scienceCommunity structureAlgorithmMathematicsStatistics

Affiliated Institutions

Related Publications

Modularity and community structure in networks

Many networks of interest in the sciences, including social networks, computer networks, and metabolic and regulatory networks, are found to divide naturally into communities or...

2006 Proceedings of the National Academy o... 11783 citations

Publication Info

Year
2004
Type
article
Volume
69
Issue
6
Pages
066133-066133
Citations
5403
Access
Closed

External Links

Social Impact

Social media, news, blog, policy document mentions

Citation Metrics

5403
OpenAlex

Cite This

M. E. J. Newman (2004). Fast algorithm for detecting community structure in networks. Physical Review E , 69 (6) , 066133-066133. https://doi.org/10.1103/physreve.69.066133

Identifiers

DOI
10.1103/physreve.69.066133