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Fast approximation of centrality Export

In SODA '01: Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms (2001), pp. 228-229.

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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.


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