  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.
