Co-Betweenness: A Pairwise Notion of Centrality

@misc{citeulike:1776037, abstract = {Betweenness centrality is a metric that seeks to quantify a sense of the importance of a vertex in a network graph in terms of its "control" on the distribution of information along geodesic paths throughout that network. This quantity however does not capture how different vertices participate together in such control. In order to allow for the uncovering of finer details in this regard, we introduce here an extension of betweenness centrality to pairs of vertices, which we term co-betweenness, that provides the basis for quantifying various analogous pairwise notions of importance and control. More specifically, we motivate and define a precise notion of co-betweenness, we present an efficient algorithm for its computation, extending the algorithm of Brandes in a natural manner, and we illustrate the utilization of this co-betweenness on a handful of different communication networks. From these real-world examples, we show that the co-betweenness allows one to identify certain vertices which are not the most central vertices but which, nevertheless, act as important actors in the relaying and dispatching of information in the network.}, author = {Kolaczyk, Eric D. and Chua, David B. and Barthelemy, Marc }, citeulike-article-id = {1776037}, eprint = {0709.3420}, keywords = {centrality, networks}, month = {Sep}, posted-at = {2007-10-16 20:10:46}, priority = {0}, title = {Co-Betweenness: A Pairwise Notion of Centrality}, url = {http://arxiv.org/abs/0709.3420}, year = {2007} }

TY - ELEC ID - citeulike:1776037 L3 - citeulike-article-id:1776037 TI - Co-Betweenness: A Pairwise Notion of Centrality N2 - Betweenness centrality is a metric that seeks to quantify a sense of the importance of a vertex in a network graph in terms of its "control" on the distribution of information along geodesic paths throughout that network. This quantity however does not capture how different vertices participate together in such control. In order to allow for the uncovering of finer details in this regard, we introduce here an extension of betweenness centrality to pairs of vertices, which we term co-betweenness, that provides the basis for quantifying various analogous pairwise notions of importance and control. More specifically, we motivate and define a precise notion of co-betweenness, we present an efficient algorithm for its computation, extending the algorithm of Brandes in a natural manner, and we illustrate the utilization of this co-betweenness on a handful of different communication networks. From these real-world examples, we show that the co-betweenness allows one to identify certain vertices which are not the most central vertices but which, nevertheless, act as important actors in the relaying and dispatching of information in the network. KW - centrality KW - networks AU - Kolaczyk, Eric AU - Chua, David AU - Barthelemy, Marc PY - 2007/Sep/21/ UR - http://arxiv.org/abs/0709.3420 ER -