Fast Approximation of Centrality
Vol. 8, no. 1, pp. 39-45, 2004. Concise paper.
Abstract Social scientists 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+ϵ) factor in ~O(m) time.
Submitted: March 2001.
Revised: March 2004.
Communicated by Martin F├╝rer
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