Can we predict citation counts of environmental modelling papers? Fourteen bibliographic and categorical variables predict less than 30% of the variability in citation counts

Robson, Barbara J., and Mousquès, Aurélie (2016) Can we predict citation counts of environmental modelling papers? Fourteen bibliographic and categorical variables predict less than 30% of the variability in citation counts. Environmental Modelling & Software, 75. pp. 94-104.

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Abstract

We assessed 6122 environmental modelling papers published since 2005 to determine whether the number of citations each paper had received by September 2014 could be predicted with no knowledge of the paper's quality. A random forest was applied, using a range of easily quantified or classified variables as predictors. The 511 papers published in two key journals in 2008 were further analysed to consider additional variables. Papers with no differential equations received more citations. The topic of the paper, number of authors and publication venue were also significant. Ten other factors, some of which have been found significant in other studies, were also considered, but most added little to the predictive power of the models. Collectively, all factors predicted 16–29% of the variation in citation counts, with the remaining variance (the majority) presumably attributable to important subjective factors such as paper quality, clarity and timeliness.

Item ID: 58048
Item Type: Article (Research - C1)
ISSN: 1873-6726
Keywords: Scientometrics, Informetrics, Bibliometrics, Citation count, Equations
Copyright Information: © 2015 Published by Elsevier Ltd.
Date Deposited: 17 Apr 2019 09:22
FoR Codes: 08 INFORMATION AND COMPUTING SCIENCES > 0807 Library and Information Studies > 080705 Informetrics @ 90%
09 ENGINEERING > 0907 Environmental Engineering > 090702 Environmental Engineering Modelling @ 10%
SEO Codes: 97 EXPANDING KNOWLEDGE > 970105 Expanding Knowledge in the Environmental Sciences @ 100%
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