Fast Approximation of Centrality
Data Structures and Algorithms
2011-03-08 v1 Disordered Systems and Neural Networks
Social and Information Networks
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+epsilon) factor in near-linear time.
Cite
@article{arxiv.cs/0009005,
title = {Fast Approximation of Centrality},
author = {David Eppstein and Joseph Wang},
journal= {arXiv preprint arXiv:cs/0009005},
year = {2011}
}
Comments
2 pages. To appear in 12th ACM/SIAM Symp. Discrete Algorithms (SODA 2001)