Publication | Open Access
Robustness of community structure in networks
345
Citations
41
References
2008
Year
EngineeringCommunity MiningNetwork AnalysisCommunicationCommunity DiscoverySmall PerturbationsComputational Social ScienceNetwork EvolutionData ScienceSuitable MethodStatisticsCommunity DetectionSocial Network AnalysisCommunity NetworkKnowledge DiscoveryComputer ScienceCommunity StructureNetwork ScienceGraph TheoryBusiness
The discovery of community structure is a common challenge in the analysis of network data. Many methods have been proposed for finding community structure, but few have been proposed for determining whether the structure found is statistically significant or whether, conversely, it could have arisen purely as a result of chance. In this paper we show that the significance of community structure can be effectively quantified by measuring its robustness to small perturbations in network structure. We propose a suitable method for perturbing networks and a measure of the resulting change in community structure and use them to assess the significance of community structure in a variety of networks, both real and computer generated.
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