An information-theoretic framework for resolving community structure in complex networks

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dc.creatorRosvall, Martin
dc.creatorBergstrom, Carl T.
dc.date2006-12-05
dc.date2007-05-02
dc.date.accessioned2026-07-07T07:59:01Z
dc.date.available2026-07-07T07:59:01Z
dc.descriptionTo understand the structure of a large-scale biological, social, or technological network, it can be helpful to decompose the network into smaller subunits or modules. In this article, we develop an information-theoretic foundation for the concept of modularity in networks. We identify the modules of which the network is composed by finding an optimal compression of its topology, capitalizing on regularities in its structure. We explain the advantages of this approach and illustrate them by partitioning a number of real-world and model networks.
dc.description5 pages, 4 figures
dc.identifierhttps://arxiv.org/abs/physics/0612035
dc.identifierhttp://arxiv.org/abs/physics/0612035
dc.identifierPNAS 104, 7327-7331 (2007)
dc.identifierdoi:10.1073/pnas.0611034104
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/128215
dc.subjectPhysics and Society
dc.subjectData Analysis, Statistics and Probability
dc.titleAn information-theoretic framework for resolving community structure in complex networks
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