Betweenness centrality is one of the most well-known measures of the importance of nodes in a social-network graph. In this paper we describe the first known external-memory and cache-oblivious algorithms for computing betweenness centrality. We present four different external-memory algorithms exhibiting various tradeoffs with respect to performance. Two of the algorithms are cache-oblivious. We describe general algorithms for networks with weighted and unweighted edges and a specialized algorithm for networks with small diameters, as is common in social networks exhibiting the “small worlds” phenomenon.
Proceedings, 2013 Ieee International Conference on Big Data, 2013, p. 368-375