A Bayesian approach for the reliability of scientific co-authorship networks with emphasis on nodes
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1016/j.socnet.2016.06.005 http://hdl.handle.net/11449/159241 |
Resumo: | The co-authorship among members of a research group commonly can be represented by a (co-authorship) graph in which nodes represent the researchers that make up of this group and edges represent the connections between two agents (i.e., the co-authorship between these agents). Current study measures the reliability of networks by taking into consideration unreliable nodes (researchers) and perfectly reliable edges (co-authorship between two researchers). A Bayesian approach for the reliability of a network represented by the co-authorship among members of a real research group is proposed, obtaining Bayesian estimates and credibility intervals for the individual components (nodes or researchers) and the network. Weakly informative and non-informative prior distributions are assumed for those components and the posterior summaries are obtained by Monte Carlo-Markov Chain methods. The results show the relevance of an inferential approach for the reliability of scientific co-authorship network. The results also demonstrate that the contribution of each researcher is highly relevant for the maintenance of a research group. In addition, the Bayesian methodology was a feasible and easy computational implementation. (C) 2016 Elsevier B.V. All rights reserved. |
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Repositório Institucional da UNESP |
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A Bayesian approach for the reliability of scientific co-authorship networks with emphasis on nodesSocial networksGraph theoryResearch,groupBayesian inferenceMCMC simulation methodsThe co-authorship among members of a research group commonly can be represented by a (co-authorship) graph in which nodes represent the researchers that make up of this group and edges represent the connections between two agents (i.e., the co-authorship between these agents). Current study measures the reliability of networks by taking into consideration unreliable nodes (researchers) and perfectly reliable edges (co-authorship between two researchers). A Bayesian approach for the reliability of a network represented by the co-authorship among members of a real research group is proposed, obtaining Bayesian estimates and credibility intervals for the individual components (nodes or researchers) and the network. Weakly informative and non-informative prior distributions are assumed for those components and the posterior summaries are obtained by Monte Carlo-Markov Chain methods. The results show the relevance of an inferential approach for the reliability of scientific co-authorship network. The results also demonstrate that the contribution of each researcher is highly relevant for the maintenance of a research group. In addition, the Bayesian methodology was a feasible and easy computational implementation. (C) 2016 Elsevier B.V. All rights reserved.Univ Estadual Paulista, BR-17602496 Tuptl, SP, BrazilUniv Sao Paulo, BR-13560970 Butanta, SP, BrazilUniv Estadual Paulista, BR-17602496 Tuptl, SP, BrazilElsevier B.V.Universidade Estadual Paulista (Unesp)Universidade de São Paulo (USP)Oliveira, Sandra Cristina [UNESP]Cobre, JulianaFerreira, Taiane de Paula [UNESP]2018-11-26T15:37:35Z2018-11-26T15:37:35Z2017-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article110-115application/pdfhttp://dx.doi.org/10.1016/j.socnet.2016.06.005Social Networks. Amsterdam: Elsevier Science Bv, v. 48, p. 110-115, 2017.0378-8733http://hdl.handle.net/11449/15924110.1016/j.socnet.2016.06.005WOS:000389730200009WOS000389730200009.pdf12689454348708140000-0002-0968-0108Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengSocial Networks2,147info:eu-repo/semantics/openAccess2023-10-12T06:07:46Zoai:repositorio.unesp.br:11449/159241Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T14:41:32.551790Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
A Bayesian approach for the reliability of scientific co-authorship networks with emphasis on nodes |
title |
A Bayesian approach for the reliability of scientific co-authorship networks with emphasis on nodes |
spellingShingle |
A Bayesian approach for the reliability of scientific co-authorship networks with emphasis on nodes Oliveira, Sandra Cristina [UNESP] Social networks Graph theory Research,group Bayesian inference MCMC simulation methods |
title_short |
A Bayesian approach for the reliability of scientific co-authorship networks with emphasis on nodes |
title_full |
A Bayesian approach for the reliability of scientific co-authorship networks with emphasis on nodes |
title_fullStr |
A Bayesian approach for the reliability of scientific co-authorship networks with emphasis on nodes |
title_full_unstemmed |
A Bayesian approach for the reliability of scientific co-authorship networks with emphasis on nodes |
title_sort |
A Bayesian approach for the reliability of scientific co-authorship networks with emphasis on nodes |
author |
Oliveira, Sandra Cristina [UNESP] |
author_facet |
Oliveira, Sandra Cristina [UNESP] Cobre, Juliana Ferreira, Taiane de Paula [UNESP] |
author_role |
author |
author2 |
Cobre, Juliana Ferreira, Taiane de Paula [UNESP] |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) Universidade de São Paulo (USP) |
dc.contributor.author.fl_str_mv |
Oliveira, Sandra Cristina [UNESP] Cobre, Juliana Ferreira, Taiane de Paula [UNESP] |
dc.subject.por.fl_str_mv |
Social networks Graph theory Research,group Bayesian inference MCMC simulation methods |
topic |
Social networks Graph theory Research,group Bayesian inference MCMC simulation methods |
description |
The co-authorship among members of a research group commonly can be represented by a (co-authorship) graph in which nodes represent the researchers that make up of this group and edges represent the connections between two agents (i.e., the co-authorship between these agents). Current study measures the reliability of networks by taking into consideration unreliable nodes (researchers) and perfectly reliable edges (co-authorship between two researchers). A Bayesian approach for the reliability of a network represented by the co-authorship among members of a real research group is proposed, obtaining Bayesian estimates and credibility intervals for the individual components (nodes or researchers) and the network. Weakly informative and non-informative prior distributions are assumed for those components and the posterior summaries are obtained by Monte Carlo-Markov Chain methods. The results show the relevance of an inferential approach for the reliability of scientific co-authorship network. The results also demonstrate that the contribution of each researcher is highly relevant for the maintenance of a research group. In addition, the Bayesian methodology was a feasible and easy computational implementation. (C) 2016 Elsevier B.V. All rights reserved. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-01-01 2018-11-26T15:37:35Z 2018-11-26T15:37:35Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1016/j.socnet.2016.06.005 Social Networks. Amsterdam: Elsevier Science Bv, v. 48, p. 110-115, 2017. 0378-8733 http://hdl.handle.net/11449/159241 10.1016/j.socnet.2016.06.005 WOS:000389730200009 WOS000389730200009.pdf 1268945434870814 0000-0002-0968-0108 |
url |
http://dx.doi.org/10.1016/j.socnet.2016.06.005 http://hdl.handle.net/11449/159241 |
identifier_str_mv |
Social Networks. Amsterdam: Elsevier Science Bv, v. 48, p. 110-115, 2017. 0378-8733 10.1016/j.socnet.2016.06.005 WOS:000389730200009 WOS000389730200009.pdf 1268945434870814 0000-0002-0968-0108 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Social Networks 2,147 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
110-115 application/pdf |
dc.publisher.none.fl_str_mv |
Elsevier B.V. |
publisher.none.fl_str_mv |
Elsevier B.V. |
dc.source.none.fl_str_mv |
Web of Science reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808128404178862080 |