Centrality metrics in social networks

Detalhes bibliográficos
Autor(a) principal: Laranjeira, Paula Alexandra
Data de Publicação: 2018
Outros Autores: Cavique, Luís
Tipo de documento: Artigo
Idioma: por
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://doi.org/10.34627/rcc.v9i0.20
Resumo: Considering models for social networks as graphs, nodes represent the actors and the edges represent the relationship between them. Influential actors are the ones that are frequently involved on relationships between other actors. This involvement makes them more visible and considered more central on the network. In this sense centrality metrics try to describe the localization properties of an important node of the network. These measures have in consideration the different interaction and communication modes an actor has with others, being more important or central the ones that are located on more strategic locations on the network. On this work it is presented the study of five centrality measures: degree, closeness, betweenness, eigenvector and katz. It is made a description of the algorithms implemented, and it is presented a case study. To complete the study it is also made a comparative analysis between results obtained with NodeXL, and the results from the algorithms implemented.
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spelling Centrality metrics in social networksMétricas de Centralidade em Redes SociaisConsidering models for social networks as graphs, nodes represent the actors and the edges represent the relationship between them. Influential actors are the ones that are frequently involved on relationships between other actors. This involvement makes them more visible and considered more central on the network. In this sense centrality metrics try to describe the localization properties of an important node of the network. These measures have in consideration the different interaction and communication modes an actor has with others, being more important or central the ones that are located on more strategic locations on the network. On this work it is presented the study of five centrality measures: degree, closeness, betweenness, eigenvector and katz. It is made a description of the algorithms implemented, and it is presented a case study. To complete the study it is also made a comparative analysis between results obtained with NodeXL, and the results from the algorithms implemented.Nos modelos de redes sociais, tal como na teoria de grafos, os vértices representam os atores e as arestas ou arcos a relação entre eles. Atores influentes são aqueles que estão frequentemente envolvidos na relação com outros atores. Este envolvimento torna-os mais visíveis sendo considerados mais centrais na rede. É neste sentido que as métricas de centralidade tentam descrever as propriedades da localização de um nó fulcral numa rede. Estas medidas têm em consideração os diferentes modos de interação e comunicação de um ator com os restantes elementos, sendo mais importantes, ou centrais, aqueles que estão localizados em posições mais estratégicas na rede. Neste trabalho apresenta-se o estudo de cinco métricas de centralidade: grau, proximidade, intermediação, vetor próprio e katz. Descrevem-se os algoritmos implementados no cálculo das medidas e apresenta-se um caso de estudo. Para completar o estudo é apresentada uma análise comparativa entre os resultados obtidos no aplicativo NodeXL, e os resultados obtidos através dos algoritmos implementados.Universidade Aberta2018-03-27info:eu-repo/semantics/articleinfo:eu-repo/semantics/otherinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://doi.org/10.34627/rcc.v9i0.20oai:ojs2.journals.uab.pt:article/20Revista de Ciências da Computação; v. 9 (2014); 1-202182-18011646-633010.34627/rcc.v9i0reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAPporhttps://journals.uab.pt/index.php/rcc/article/view/20https://doi.org/10.34627/rcc.v9i0.20https://journals.uab.pt/index.php/rcc/article/view/20/35Direitos de Autor (c) 2018 Universidade Abertahttp://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessLaranjeira, Paula AlexandraCavique, Luís2022-10-25T11:31:49Zoai:ojs2.journals.uab.pt:article/20Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T16:13:57.292262Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Centrality metrics in social networks
Métricas de Centralidade em Redes Sociais
title Centrality metrics in social networks
spellingShingle Centrality metrics in social networks
Laranjeira, Paula Alexandra
title_short Centrality metrics in social networks
title_full Centrality metrics in social networks
title_fullStr Centrality metrics in social networks
title_full_unstemmed Centrality metrics in social networks
title_sort Centrality metrics in social networks
author Laranjeira, Paula Alexandra
author_facet Laranjeira, Paula Alexandra
Cavique, Luís
author_role author
author2 Cavique, Luís
author2_role author
dc.contributor.author.fl_str_mv Laranjeira, Paula Alexandra
Cavique, Luís
description Considering models for social networks as graphs, nodes represent the actors and the edges represent the relationship between them. Influential actors are the ones that are frequently involved on relationships between other actors. This involvement makes them more visible and considered more central on the network. In this sense centrality metrics try to describe the localization properties of an important node of the network. These measures have in consideration the different interaction and communication modes an actor has with others, being more important or central the ones that are located on more strategic locations on the network. On this work it is presented the study of five centrality measures: degree, closeness, betweenness, eigenvector and katz. It is made a description of the algorithms implemented, and it is presented a case study. To complete the study it is also made a comparative analysis between results obtained with NodeXL, and the results from the algorithms implemented.
publishDate 2018
dc.date.none.fl_str_mv 2018-03-27
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/other
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://doi.org/10.34627/rcc.v9i0.20
oai:ojs2.journals.uab.pt:article/20
url https://doi.org/10.34627/rcc.v9i0.20
identifier_str_mv oai:ojs2.journals.uab.pt:article/20
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://journals.uab.pt/index.php/rcc/article/view/20
https://doi.org/10.34627/rcc.v9i0.20
https://journals.uab.pt/index.php/rcc/article/view/20/35
dc.rights.driver.fl_str_mv Direitos de Autor (c) 2018 Universidade Aberta
http://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Direitos de Autor (c) 2018 Universidade Aberta
http://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Aberta
publisher.none.fl_str_mv Universidade Aberta
dc.source.none.fl_str_mv Revista de Ciências da Computação; v. 9 (2014); 1-20
2182-1801
1646-6330
10.34627/rcc.v9i0
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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