Journal
JOURNAL OF INFORMETRICS
Volume 12, Issue 2, Pages 401-415Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.joi.2018.02.002
Keywords
Citation analysis; Characteristic scores and scales (CSS); Lognormal distribution; Universality claim
Funding
- Research Institute of the University of Bucharest
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Characteristic scores and scales (CSS) - a well-established scientometric tool for the study of citation counts - have been used to document a striking phenomenon that characterizes citation distributions at high levels of aggregation: irrespective of scientific field and citation window empirical studies find a persistent pattern whereby about 70% of scientific papers belong to the class of poorly cited papers, about 21% belong to the class of fairly cited papers, 6% to that of remarkably cited papers and 3% to the class of outstandingly cited papers. This article aims to advance the understanding of this remarkable result by examining it in the context of the lognormal distribution, a popular model used to describe citation counts across scientific fields. The article shows that the application of the CSS method to lognormal distributions provides a very good fit to the 70-21-6-3% empirical pattern provided these distributions are characterized by a standard deviation parameter in the range of about 0.8-1.3. The CSS pattern is essentially explainable as an epiphenomenon of the lognormal functional form and, more generally, as a consequence of the skewness of science which is manifest in heavy-tailed citation distributions. (C) 2018 Elsevier Ltd. All rights reserved.
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