Community structure in social and biological networks

DOI Web Site 被引用文献136件
  • M. Girvan
    Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501; Department of Physics, Cornell University, Clark Hall, Ithaca, NY 14853-2501; and Department of Physics, University of Michigan, Ann Arbor, MI 48109-1120
  • M. E. J. Newman
    Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501; Department of Physics, Cornell University, Clark Hall, Ithaca, NY 14853-2501; and Department of Physics, University of Michigan, Ann Arbor, MI 48109-1120

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<jats:p>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 using centrality indices to find community boundaries. We test our method on computer-generated and real-world graphs whose community structure is already known and find that 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 collaboration network and a food web—and find that it detects significant and informative community divisions in both cases.</jats:p>

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