Discriminating Power of Centrality Measures in Complex Networks.

Abstract

Centrality metrics are one of the most fundamental tools in social network analysis and network science, and various measures for evaluating node importance metrics have been devised. However, the crucial issue of testing the discriminating power of different centrality measures is still open. In this article, we propose to assess the discriminating power of node centrality measures by using the notion of automorphism and orbit: nodes in the same orbit have identical metric scores, while nodes in different orbits should have different centrality values. Under this assumption, we present a benchmark for the discriminating power of node centrality measures. Moreover, we propose an efficient approach to evaluate centrality measures in terms of the discriminating power, which is devoid of finding orbits. Extensive experiments on real and model networks are executed to compare seven commonly used node centrality metrics.