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# Fast approximation of betweenness centrality through sampling

@article{Riondato2014FastAO, title={Fast approximation of betweenness centrality through sampling}, author={Matteo Riondato and Evgenios M. Kornaropoulos}, journal={Data Mining and Knowledge Discovery}, year={2014}, volume={30}, pages={438-475} }

- Published in Data Mining and Knowledge Discovery 2014
DOI:10.1007/s10618-015-0423-0

Betweenness centrality is a fundamental measure in social network analysis, expressing the importance or influence of individual vertices in a network in terms of the fraction of shortest paths that pass through them. Exact computation in large networks is prohibitively expensive and fast approximation algorithms are required in these cases. We present two efficient randomized algorithms for betweenness estimation. The algorithms are based on random sampling of shortest paths and offer… CONTINUE READING

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