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How to Measure the Researcher Impact with the Aid of its Impactable Area: A Concrete Approach Using Distance Geometry

Author

Listed:
  • Beniamino Cappelletti-Montano

    (University of Cagliari)

  • Gianmarco Cherchi

    (University of Cagliari)

  • Benedetto Manca

    (University of Cagliari)

  • Stefano Montaldo

    (University of Cagliari)

  • Monica Musio

    (University of Cagliari)

Abstract

Assuming that the subject of each scientific publication can be identified by one or more classification entities, we address the problem of determining a similarity function (distance) between classification entities based on how often two classification entities are used in the same publication. This similarity function is then used to obtain a representation of the classification entities as points of an Euclidean space of a suitable dimension by means of optimization and dimensionality reduction algorithms. This procedure allows us also to represent the researchers as points in the same Euclidean space and to determine the distance between researchers according to their scientific production. As a case study, we consider as classification entities the codes of the American Mathematical Society Classification System.

Suggested Citation

  • Beniamino Cappelletti-Montano & Gianmarco Cherchi & Benedetto Manca & Stefano Montaldo & Monica Musio, 2025. "How to Measure the Researcher Impact with the Aid of its Impactable Area: A Concrete Approach Using Distance Geometry," Journal of Classification, Springer;The Classification Society, vol. 42(1), pages 253-281, March.
    • Handle: RePEc:spr:jclass:v:42:y:2025:i:1:d:10.1007_s00357-024-09490-2
    DOI: 10.1007/s00357-024-09490-2
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    References listed on IDEAS

    as
    1. Lutz Bornmann & Robin Haunschild, 2018. "Plots for visualizing paper impact and journal impact of single researchers in a single graph," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(1), pages 385-394, April.
    2. Cappelletti-Montano, Beniamino & Columbu, Silvia & Montaldo, Stefano & Musio, Monica, 2021. "New perspectives in bibliometric indicators: Moving from citations to citing authors," Journal of Informetrics, Elsevier, vol. 15(3).
    3. Leo Liberti, 2020. "Rejoinder on: Distance geometry and data science," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(2), pages 350-357, July.
    4. Ludo Waltman & Nees Jan Eck, 2013. "Source normalized indicators of citation impact: an overview of different approaches and an empirical comparison," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(3), pages 699-716, September.
    5. Baccini, Federica & Barabesi, Lucio & Baccini, Alberto & Khelfaoui, Mahdi & Gingras, Yves, 2022. "Similarity network fusion for scholarly journals," Journal of Informetrics, Elsevier, vol. 16(1).
    6. Lutz Bornmann & Werner Marx, 2014. "How to evaluate individual researchers working in the natural and life sciences meaningfully? A proposal of methods based on percentiles of citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(1), pages 487-509, January.
    7. repec:plo:pbio00:3000384 is not listed on IDEAS
    8. Camil Demetrescu & Irene Finocchi & Andrea Ribichini & Marco Schaerf, 2020. "On bibliometrics in academic promotions: a case study in computer science and engineering in Italy," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 2207-2228, September.
    9. Marzolla, Moreno, 2016. "Assessing evaluation procedures for individual researchers: The case of the Italian National Scientific Qualification," Journal of Informetrics, Elsevier, vol. 10(2), pages 408-438.
    10. Fionn Murtagh & Michael Orlov & Boris Mirkin, 2018. "Qualitative Judgement of Research Impact: Domain Taxonomy as a Fundamental Framework for Judgement of the Quality of Research," Journal of Classification, Springer;The Classification Society, vol. 35(1), pages 5-28, April.
    11. Robin Haunschild & Lutz Bornmann & Jonathan Adams, 2019. "R package for producing beamplots as a preferred alternative to the h index when assessing single researchers (based on downloads from Web of Science)," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(2), pages 925-927, August.
    12. Leo Liberti, 2020. "Distance geometry and data science," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(2), pages 271-339, July.
    13. Alberto Baccini & Giuseppe De Nicolao & Eugenio Petrovich, 2019. "Citation gaming induced by bibliometric evaluation: A country-level comparative analysis," PLOS ONE, Public Library of Science, vol. 14(9), pages 1-16, September.
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