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Neighborhoods are good communities

D. Gleich,C. Seshadhri

Published 2011 in arXiv.org

ABSTRACT

The communities of a social network are sets of vertices with more connections inside the set than outside. We theoretically demonstrate that two commonly observed properties of social networks, heavy-tailed degree distributions and large clustering coefficients, imply the existence of vertex neighborhoods (also known as egonets) that are themselves good communities. We evaluate these neighborhood communities on a range of graphs. What we find is that the neighborhood communities often exhibit conductance scores that are as good as the Fiedler cut. Also, the conductance of neighborhood communities shows similar behavior as the network community profile computed with a personalized PageRank community detection method. The latter requires sweeping over a great many starting vertices, which can be expensive. By using a small and easy-to-compute set of neighborhood communities as seeds for these PageRank communities, however, we find communities that precisely capture the behavior of the network community profile when seeded everywhere in the graph, and at a significant reduction in total work.

PUBLICATION RECORD

  • Publication year

    2011

  • Venue

    arXiv.org

  • Publication date

    2011-11-01

  • Fields of study

    Mathematics, Physics, Computer Science

  • Identifiers
    arXiv 1112.0031
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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REFERENCES

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