Clustering as a measure of the local topology of networks

Abstract

Usual formulations of the clustering coefficient can be shown to be insufficient in the task of describing the local topology of very simple networks. Motivated by this, we review some alternatives in order to present an extension, the clustering profile. We show, both conceptually and through applications to well studied networks, that this measure is a more complete and robust measure of clustering. It imposes stringent constraints on theoretical growth models, specially on aspects of the network structure that play a central role in dynamics on networks. In addition, we study how it provides a richer perspective of phenomena such as hierarchy, small-worlds and clusterization.