Volume 75, January 01, 2016, Pages 94-104
Can we predict citation
counts of environmental modelling papers? Fourteen bibliographic and
categorical variables predict less than 30% of the variability in
citation counts (Article)
CSIRO Land and Water, GPO Box 1666, Canberra, ACT, Australia
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. © 2015 Published by Elsevier Ltd.
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. © 2015 Published by Elsevier Ltd.
Author keywords
Bibliometrics; Citation count; Equations; Informetrics; Scientometrics
ISSN: 13648152
CODEN: EMSOFSource Type: Journal
Original language: English
DOI: 10.1016/j.envsoft.2015.10.007Document Type: Article
Publisher: Elsevier Ltd
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References
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Ebrahim, N.A., Salehi, H., Embi, M.A., Tanha, F.H., Gholizadeh, H., Motahar, S.M., Ordi, A.
Effective strategies for increasing citation frequency
(2013) International Education Studies, 6 (11), pp. 93-99. Cited 9 times.
http://ccsenet.org/journal/index.php/ies/article/download/30366/18385
doi: 10.5539/ies.v6n11p93
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