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Toward a stochastically robust normalized impact factor against fraud and scams

Author

Listed:
  • Khaled Belkadhi

    (South Mediterranean University
    Université Tunis El Manar)

  • Adel Trabelsi

    (Université Tunis El Manar
    Centre National de Sciences et de Technologies Nucléaires)

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.

Suggested Citation

  • Khaled Belkadhi & Adel Trabelsi, 2020. "Toward a stochastically robust normalized impact factor against fraud and scams," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 1871-1884, September.
    • Handle: RePEc:spr:scient:v:124:y:2020:i:3:d:10.1007_s11192-020-03577-4
    DOI: 10.1007/s11192-020-03577-4
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    References listed on IDEAS

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    3. Thed N. van Leeuwen & Henk F. Moed, 2002. "Development and application of journal impact measures in the Dutch science system," Scientometrics, Springer;Akadémiai Kiadó, vol. 53(2), pages 249-266, February.
    4. Maria Bordons & M. T. Fernández & Isabel Gómez, 2002. "Advantages and limitations in the use of impact factor measures for the assessment of research performance," Scientometrics, Springer;Akadémiai Kiadó, vol. 53(2), pages 195-206, February.
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