Toward a stochastically robust normalized impact factor against fraud and scams

Khaled Belkadhi () and Adel Trabelsi ()
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Khaled Belkadhi: South Mediterranean University
Adel Trabelsi: Université Tunis El Manar

Scientometrics, 2020, vol. 124, issue 3, No 8, 1884 pages

Abstract: Abstract In this paper, we model the variation of the bibliometric measure differences across academic fields in order to quantify the sources of these discrepancies. Since the bibliometric measure is based on the amount of published and cited papers, we anticipate that the mean number of references by published paper is the predominant parameter behind the discrepancies of impact factor scores in some academic fields. We introduce here a bias-free model, based on normalized variables with restricted cross-discipline discrepancies, that is robust against fraud and scams. The model is then submitted to an intensive numerical test using a Monte Carlo simulation.

Keywords: Impact factor; Monte Carlo simulation; Normalization (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s11192-020-03577-4

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