Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/129964
Título: A field‑ and time‑normalized Bayesian approach to measuring the impact of a publication
Autores/as: Gómez Déniz, Emilio 
Dorta González, Pablo 
Clasificación UNESCO: 570106 Documentación
5302 Econometría
Palabras clave: Normalized citation impact
Field normalization
Time normalization
Bayesian score
Citation obsolescence, et al.
Fecha de publicación: 2024
Proyectos: Evaluación Económicay Meta-Análisis: Soluciones Bayesianas en Economía de la Salud 
Publicación seriada: Scientometrics 
Resumen: Measuring the impact of a publication in a fair way is a significant challenge in bibliometrics, as it must not introduce biases between fields and should enable comparison of the impact of publications from different years. In this paper, we propose a Bayesian approach to tackle this problem, motivated by empirical data demonstrating heterogeneity in citation distributions. The approach uses the a priori distribution of citations in each field to estimate the expected a posteriori distribution in that field. This distribution is then employed to normalize the citations received by a publication in that field. Our main contribution is the Bayesian Impact Score, a measure of the impact of a publication. This score is increasing and concave with the number of citations received and decreasing and convex with the age of the publication. This means that the marginal score of an additional citation decreases as the cumulative number of citations increases and increases as the time since publication of the document grows. Finally, we present an empirical application of our approach in eight subject categories using the Scopus database and a comparison with the normalized impact indicator Field Citation Ratio from the Dimensions AI database.
URI: http://hdl.handle.net/10553/129964
ISSN: 0138-9130
DOI: 10.1007/s11192-024-04997-2
Fuente: Scientometrics [ISSN 0138-9130], v. 129, n. 5, p. 2659-2676, (Mayo 2024)
Colección:Artículos
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