  The recent high level of interest in weighted complex networks gives rise to
a need to develop new measures and to generalize existing ones to take the
weights of links into account. Here we focus on various generalizations of the
clustering coefficient, which is one of the central characteristics in the
complex network theory. We present a comparative study of the several
suggestions introduced in the literature, and point out their advantages and
limitations. The concepts are illustrated by simple examples as well as by
empirical data of the world trade and weighted coauthorship networks.

Statistical Mechanics;Disordered Systems and Neural Networks;Physics and Society