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Statistical validation of a global model for the distribution of the ultimate number of citations accrued by papers published in a scientific journal

A central issue in evaluative bibliometrics is the characterization of the citation distribution of papers in the scientific literature. Here, we perform a large-scale empirical analysis of journals from every field in Thomson Reuters' Web of Science database. We find that only 30 of the 2,184...

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Detalles Bibliográficos
Autores principales: Stringer, Michael J, Sales-Pardo, Marta, Amaral, Luís A Nunes
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wiley Subscription Services, Inc., A Wiley Company 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3158611/
https://www.ncbi.nlm.nih.gov/pubmed/21858251
http://dx.doi.org/10.1002/asi.21335
Descripción
Sumario:A central issue in evaluative bibliometrics is the characterization of the citation distribution of papers in the scientific literature. Here, we perform a large-scale empirical analysis of journals from every field in Thomson Reuters' Web of Science database. We find that only 30 of the 2,184 journals have citation distributions that are inconsistent with a discrete lognormal distribution at the rejection threshold that controls the false discovery rate at 0.05. We find that large, multidisciplinary journals are over-represented in this set of 30 journals, leading us to conclude that, within a discipline, citation distributions are lognormal. Our results strongly suggest that the discrete lognormal distribution is a globally accurate model for the distribution of “eventual impact” of scientific papers published in single-discipline journal in a single year that is removed sufficiently from the present date.