Publicação: A Bayesian approach for the reliability of scientific co-authorship networks with emphasis on nodes
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Elsevier B.V.
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Acesso aberto
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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Social networks, Graph theory, Research,group, Bayesian inference, MCMC simulation methods
Idioma
Inglês
Como citar
Social Networks. Amsterdam: Elsevier Science Bv, v. 48, p. 110-115, 2017.
