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Ranking authors using fractional counting of citations: An axiomatic approach

Author

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  • Denis Bouyssou

    (LAMSADE - Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision - Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres - CNRS - Centre National de la Recherche Scientifique)

  • Thierry Marchant

    (Department of Data Analysis - UGent - Universiteit Gent = Ghent University = Université de Gand)

Abstract

This paper analyzes from an axiomatic point of view a recent proposal for counting citations: the value of a citation given by a paper is inversely proportional to the total number of papers it cites. This way of fractionally counting citations was suggested as a possible way to normalize citation counts between fields of research having different citation cultures. It belongs to the "citing-side" approach to normalization. We focus on the properties characterizing this way of counting citations when it comes to ranking authors. Our analysis is conducted within a formal framework that is more complex but also more realistic than the one usually adopted in most axiomatic analyses of this kind.

Suggested Citation

  • Denis Bouyssou & Thierry Marchant, 2016. "Ranking authors using fractional counting of citations: An axiomatic approach," Post-Print hal-01397699, HAL.
    • Handle: RePEc:hal:journl:hal-01397699
    DOI: 10.1016/j.joi.2015.12.006
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    Cited by:

    1. Csomós, György, 2020. "Introducing recalibrated academic performance indicators in the evaluation of individuals’ research performance: A case study from Eastern Europe," Journal of Informetrics, Elsevier, vol. 14(4).
    2. Dunaiski, Marcel & Geldenhuys, Jaco & Visser, Willem, 2018. "How to evaluate rankings of academic entities using test data," Journal of Informetrics, Elsevier, vol. 12(3), pages 631-655.
    3. Nisar Ali & Zahid Halim & Syed Fawad Hussain, 2023. "An artificial intelligence-based framework for data-driven categorization of computer scientists: a case study of world’s Top 10 computing departments," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(3), pages 1513-1545, March.
    4. Sylvain Béal & Eric Rémila & Philippe Solal & Sylvain Ferrières, 2016. "An axiomatization of the iterated h-index and applications to sport rankings," Working Papers hal-01394818, HAL.
    5. Osório, António (António Miguel), 2019. "The value and credits of n-authors publications," Working Papers 2072/376026, Universitat Rovira i Virgili, Department of Economics.
    6. Raminta Pranckutė, 2021. "Web of Science (WoS) and Scopus: The Titans of Bibliographic Information in Today’s Academic World," Publications, MDPI, vol. 9(1), pages 1-59, March.
    7. Jianhua Hou & Da Ma, 2020. "How the high-impact papers formed? A study using data from social media and citation," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2597-2615, December.
    8. Sziklai, Balázs R., 2021. "Ranking institutions within a discipline: The steep mountain of academic excellence," Journal of Informetrics, Elsevier, vol. 15(2).
    9. Mark Levene & Trevor Fenner & Judit Bar-Ilan, 2019. "Characterisation of the $$\chi$$χ-index and the rec-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(2), pages 885-896, August.
    10. Wang, Xing & Zhang, Zhihui, 2020. "Improving the reliability of short-term citation impact indicators by taking into account the correlation between short- and long-term citation impact," Journal of Informetrics, Elsevier, vol. 14(2).
    11. Antonin Macé, 2023. "The Limits of Citation Counts," Working Papers halshs-01630095, HAL.
    12. L'aszl'o Csat'o, 2019. "Journal ranking should depend on the level of aggregation," Papers 1904.06300, arXiv.org, revised Sep 2019.
    13. Louis-Stéphane Clercq, 2024. "ABCal: a Python package for author bias computation and scientometric plotting for reviews and meta-analyses," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(1), pages 581-600, January.
    14. Fabio Zagonari, 2019. "Scientific Production and Productivity for Characterizing an Author’s Publication History: Simple and Nested Gini’s and Hirsch’s Indexes Combined," Publications, MDPI, vol. 7(2), pages 1-30, May.
    15. Prathap, Gangan & Ujum, Ephrance Abu & Kumar, Sameer & Ratnavelu, Kuru, 2021. "Scoring the resourcefulness of researchers using bibliographic coupling patterns," Journal of Informetrics, Elsevier, vol. 15(3).
    16. Csató, László, 2019. "Journal ranking should depend on the level of aggregation," Journal of Informetrics, Elsevier, vol. 13(4).

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