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Phys Rev E Stat Nonlin Soft Matter Phys. 2007 Feb;75(2 Pt 2):027105. Epub 2007 Feb 23.

Generalizations of the clustering coefficient to weighted complex networks.

Author information

1
Laboratory of Computational Engineering, Helsinki University of Technology, P.O. Box 9203, FIN-02015 HUT, Finland. jsaramak@lce.hut.fi

Abstract

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.

PMID:
17358454
DOI:
10.1103/PhysRevE.75.027105

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