Clustering in weighted networks

被引:672
作者
Opsahl, Tore [1 ]
Panzarasa, Pietro [1 ]
机构
[1] Queen Mary Univ London, Sch Business & Management, London E1 4NS, England
关键词
Clustering; Transitivity; Weighted networks; TESTING TRANSITIVITY; SOCIAL NETWORK; MODELS; ORGANIZATION; MODULARITY; EVOLUTION; PATTERNS; STRENGTH;
D O I
10.1016/j.socnet.2009.02.002
中图分类号
Q98 [人类学];
学科分类号
030303 ;
摘要
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. (C) 2009 Elsevier B.V. All rights reserved.
引用
收藏
页码:155 / 163
页数:9
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