Fast approximation of centrality

  • Authors:
  • David Eppstein;Joseph Wang

  • Affiliations:
  • Dept. Inf. & Comp. Sci., UC Irvine, CA;Dept. Inf. & Comp. Sci., UC Irvine, CA

  • Venue:
  • SODA '01 Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
  • Year:
  • 2001

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Abstract

Social studies researchers use graphs to model group activities in social networks. An important property in this context is the centrality of a vertex: the inverse of the average distance to each other vertex. We describe a randomized approximation algorithm for centrality in weighted graphs. For graphs exhibiting the small world phenomenon, our method estimates the centrality of all vertices with high probability within a (1 + ∈) factor in near-linear time.