Community detection in networks

Autores
Dorso, Claudio Oscar; Medus, A. D.
Año de publicación
2010
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The 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.
Fil: Dorso, Claudio Oscar. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina
Fil: Medus, A. D.. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina
Materia
Bottlenose Dolphins Network
Community Structures
Complex Networks
Zachary Karate Club Network
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/60555
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Community detection in networksDorso, Claudio OscarMedus, A. D.Bottlenose Dolphins NetworkCommunity StructuresComplex NetworksZachary Karate Club Networkhttps://purl.org/becyt/ford/1.3https://purl.org/becyt/ford/1The 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.Fil: Dorso, Claudio Oscar. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaFil: Medus, A. D.. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; ArgentinaWorld Scientific2010-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/60555Dorso, Claudio Oscar; Medus, A. D.; Community detection in networks; World Scientific; International Journal Of Bifurcation And Chaos; 20; 2; 4-2010; 361-3670218-1274CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1142/S0218127410025818info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:20:45Zoai:ri.conicet.gov.ar:11336/60555instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:20:45.607CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Community detection in networks
title Community detection in networks
spellingShingle Community detection in networks
Dorso, Claudio Oscar
Bottlenose Dolphins Network
Community Structures
Complex Networks
Zachary Karate Club Network
title_short Community detection in networks
title_full Community detection in networks
title_fullStr Community detection in networks
title_full_unstemmed Community detection in networks
title_sort Community detection in networks
dc.creator.none.fl_str_mv Dorso, Claudio Oscar
Medus, A. D.
author Dorso, Claudio Oscar
author_facet Dorso, Claudio Oscar
Medus, A. D.
author_role author
author2 Medus, A. D.
author2_role author
dc.subject.none.fl_str_mv Bottlenose Dolphins Network
Community Structures
Complex Networks
Zachary Karate Club Network
topic Bottlenose Dolphins Network
Community Structures
Complex Networks
Zachary Karate Club Network
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.3
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The 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.
Fil: Dorso, Claudio Oscar. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina
Fil: Medus, A. D.. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina
description The 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.
publishDate 2010
dc.date.none.fl_str_mv 2010-04
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/60555
Dorso, Claudio Oscar; Medus, A. D.; Community detection in networks; World Scientific; International Journal Of Bifurcation And Chaos; 20; 2; 4-2010; 361-367
0218-1274
CONICET Digital
CONICET
url http://hdl.handle.net/11336/60555
identifier_str_mv Dorso, Claudio Oscar; Medus, A. D.; Community detection in networks; World Scientific; International Journal Of Bifurcation And Chaos; 20; 2; 4-2010; 361-367
0218-1274
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1142/S0218127410025818
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv World Scientific
publisher.none.fl_str_mv World Scientific
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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