Network Science · 2015 · 39 citations · 11 references
Community StructureCluster ComputingClustering CoefficientNetwork ScienceGraph TheoryWeighted NetworksData MiningEngineeringBusinessNetwork AnalysisCommunity MiningNew DefinitionLarge-scale NetworkNetwork TheorySocial Network AnalysisCluster Technology
Abstract The clustering coefficient is typically used as a measure of the prevalence of node clusters in a network. Various definitions for this measure have been proposed for the cases of networks having weighted edges which may or not be directed. However, these techniques consistently assume that only a subset of all possible edges is present in the network, whereas there are weighted networks of interest in which all possible edges are present, that is, complete weighted networks. For this situation, the concept of clustering is redefined, and computational techniques are presented for computing an associated clustering coefficient for complete weighted undirected or directed networks. The performance of this new definition is compared with that of current clustering definitions when extended to complete weighted networks.
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