Can
we predict citation counts of environmental modelling papers? Fourteen
bibliographic and categorical variables predict less than 30% of the
variability in citation counts
- Received 9 January 2015, Revised 6 October 2015, Accepted 7 October 2015, Available online 11 November 2015
Highlights
- •
- 6122 environmental modelling papers were assessed to determine factors associated with high citation counts.
- •
- Topic modelling identified seven clusters of papers related by subject.
- •
- We also assessed 5 very highly cited papers to examine why they were cited.
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- Papers containing differential equations received fewer citations than those without.
- •
- Papers relating to topics that cross disciplinary boundaries received more citations.
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.
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.
Keywords
- Scientometrics;
- Informetrics;
- Bibliometrics;
- Citation count;
- Equations
Can we predict citation counts of environmental modelling papers? Fourteen bibliographic and categorical variables predict less than 30% of the variability in citation counts
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