Community detection in networks

dc.creatorDorso, Claudio Oscar
dc.creatorMedus, A. D.
dc.date.accessioned2018-09-21T14:24:33Z
dc.date.accessioned2018-11-06T14:37:37Z
dc.date.available2018-09-21T14:24:33Z
dc.date.available2018-11-06T14:37:37Z
dc.date.created2018-09-21T14:24:33Z
dc.date.issued2010-04
dc.identifierDorso, Claudio Oscar; Medus, A. D.; Community detection in networks; World Scientific; International Journal Of Bifurcation And Chaos; 20; 2; 4-2010; 361-367
dc.identifier0218-1274
dc.identifierhttp://hdl.handle.net/11336/60555
dc.identifierCONICET Digital
dc.identifierCONICET
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1888370
dc.description.abstractThe problem of community detection is relevant in many disciplines of science. A community is usually defined, in a qualitative way, as a subset of nodes of a network which are more connected among themselves than to the rest of the network. In this article, we introduce a new method for community detection in complex networks. We define new merit factors based on the weak and strong community definitions formulated by Radicchi et al. [2004] and we show that this local definition properly describes the communities observed experimentally in two typical social networks. © 2010 World Scientific Publishing Company.
dc.languageeng
dc.publisherWorld Scientific
dc.relationinfo:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1142/S0218127410025818
dc.rightshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subjectBOTTLENOSE DOLPHINS NETWORK
dc.subjectCOMMUNITY STRUCTURES
dc.subjectCOMPLEX NETWORKS
dc.subjectZACHARY KARATE CLUB NETWORK
dc.titleCommunity detection in networks
dc.typeArtículos de revistas
dc.typeArtículos de revistas
dc.typeArtículos de revistas


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