Detection of node group membership in networks with group overlap

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dc.creatorSawardecker, Erin N.
dc.creatorSales-Pardo, Marta
dc.creatorAmaral, Luís A. Nunes
dc.date2008-12-05
dc.date.accessioned2026-07-07T13:10:21Z
dc.date.available2026-07-07T13:10:21Z
dc.descriptionMost networks found in social and biochemical systems have modular structures. An important question prompted by the modularity of these networks is whether nodes can be said to belong to a single group. If they cannot, we would need to consider the role of "overlapping communities." Despite some efforts in this direction, the problem of detecting overlapping groups remains unsolved because there is neither a formal definition of overlapping community, nor an ensemble of networks with which to test the performance of group detection algorithms when nodes can belong to more than one group. Here, we introduce an ensemble of networks with overlapping groups. We then apply three group identification methods--modularity maximization, k-clique percolation, and modularity-landscape surveying--to these networks. We find that the modularity-landscape surveying method is the only one able to detect heterogeneities in node memberships, and that those heterogeneities are only detectable when the overlap is small. Surprisingly, we find that the k-clique percolation method is unable to detect node membership for the overlapping case.
dc.description12 pages, 6 figures. To appear in Euro. Phys. J B
dc.identifierhttps://arxiv.org/abs/0812.1243
dc.identifierhttp://arxiv.org/abs/0812.1243
dc.identifierEur. Phys. J B 67, 277--284 (2009)
dc.identifierdoi:10.1140/epjb/e2008-00418-0
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/228994
dc.subjectData Analysis, Statistics and Probability
dc.subjectPhysics and Society
dc.titleDetection of node group membership in networks with group overlap
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