Clustering in weighted networks

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 th...

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Bibliographic Details
Published in:Social networks 2009-05, Vol.31 (2), p.155-163
Main Authors: Opsahl, Tore, Panzarasa, Pietro
Format: Article
Language:English
Subjects:
Cluster analysis
Clustering
Coefficients
Difference
History, theory and methodology
Information
Methodology
Network Analysis
Networks
Social Networks
Sociology
Structural analysis
Transitivity
Weighted networks
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Summary: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.
ISSN:0378-8733
1879-2111
DOI:10.1016/j.socnet.2009.02.002