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Generalizations of the clustering coefficient to weighted complex networks

Physical Review E · 2007 · Vol. 75(2) · pp. 027105–027105

Jari Saramäki✉(Helsinki Institute of Physics)Mikko Kivelä(Helsinki Institute of Physics)Jukka‐Pekka Onnela(University of Oxford)Kimmo Kaski(Helsinki Institute of Physics)János Kertész(Budapest University of Technology and Economics)

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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.

Complex Network Analysis Techniques Opinion Dynamics and Social Influence Bioinformatics and Genomic NetworksClustering coefficientCluster analysisComplex networkComputer scienceFocus (optics)Simple (philosophy)Point (geometry)Data miningTheoretical computer scienceArtificial intelligence

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