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Clustering in weighted networks

Social NetworksPublished 14 March 2009
Tore Opsahl, Pietro Panzarasa
Citations1,026
SJR quartileQ1
SJR score1.17
SNIP1.50

TL;DR

This paper focuses on a measure originally defined for unweighted networks: the global clustering coefficient, and proposes a generalization of this coefficient that retains the information encoded in the weights of ties.

Abstract

In recent years, researchers have investigated a growing number of weighted networks where ties are differentiated according to their strength or capacity. Yet, most network measures do not take weights into consideration, and thus do not fully capture the richness of the information contained in the data. In this paper, we focus on a measure originally defined for unweighted networks: the global clustering coefficient. We propose a generalization of this coefficient that retains the information encoded in the weights of ties. We then undertake a comparative assessment by applying the standard and generalized coefficients to a number of network datasets.

Keywords

Computer SciencePhysics and Astronomy