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Analysis of bibliometric indicators for individual scholars in a large data set

Author

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  • Filippo Radicchi

    (Universitat Rovira i Virgili)

  • Claudio Castellano

    (Istituto dei Sistemi Complessi (ISC-CNR)
    Sapienza Universitá di Roma)

Abstract

Citation numbers and other quantities derived from bibliographic databases are becoming standard tools for the assessment of productivity and impact of research activities. Though widely used, still their statistical properties have not been well established so far. This is especially true in the case of bibliometric indicators aimed at the evaluation of individual scholars, because large-scale data sets are typically difficult to be retrieved. Here, we take advantage of a recently introduced large bibliographic data set, Google Scholar Citations, which collects the entire publication record of individual scholars. We analyze the scientific profile of more than 30,000 researchers, and study the relation between the h-index, the number of publications and the number of citations of individual scientists. While the number of publications of a scientist has a rather weak relation with his/her h-index, we find that the h-index of a scientist is strongly correlated with the number of citations that she/he has received so that the number of citations can be effectively be used as a proxy of the h-index. Allowing for the h-index to depend on both the number of citations and the number of publications, we find only a minor improvement.

Suggested Citation

  • Filippo Radicchi & Claudio Castellano, 2013. "Analysis of bibliometric indicators for individual scholars in a large data set," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(3), pages 627-637, December.
    • Handle: RePEc:spr:scient:v:97:y:2013:i:3:d:10.1007_s11192-013-1027-3
    DOI: 10.1007/s11192-013-1027-3
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    6. Ghosh, Asim & Chakrabarti, Bikas K., 2023. "Scaling and kinetic exchange like behavior of Hirsch index and total citation distributions: Scopus-CiteScore data analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 626(C).
    7. Gustavo Vicentis Oliveira Fernandes & Juliana Campos Hasse Fernandes, 2024. "GFsa (GF “Scientific Age”) Index Application for Assessment of 1020 Highly Cited Researchers in Dentistry: A Pilot Study Comparing GFsa Index and H-Index," Publications, MDPI, vol. 12(2), pages 1-11, June.
    8. Kaur, Jasleen & Radicchi, Filippo & Menczer, Filippo, 2014. "On the use of sampling statistics to advance bibliometrics," Journal of Informetrics, Elsevier, vol. 8(2), pages 419-420.
    9. Tokmachev, Andrey M., 2023. "Hidden scales in statistics of citation indicators," Journal of Informetrics, Elsevier, vol. 17(1).
    10. Nane, Gabriela F. & Larivière, Vincent & Costas, Rodrigo, 2017. "Predicting the age of researchers using bibliometric data," Journal of Informetrics, Elsevier, vol. 11(3), pages 713-729.
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    16. Lucio Bertoli-Barsotti & Tommaso Lando, 2017. "A theoretical model of the relationship between the h-index and other simple citation indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1415-1448, June.
    17. 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.
    18. Díaz-Faes, Adrián A. & Costas, Rodrigo & Galindo, M. Purificación & Bordons, María, 2015. "Unravelling the performance of individual scholars: Use of Canonical Biplot analysis to explore the performance of scientists by academic rank and scientific field," Journal of Informetrics, Elsevier, vol. 9(4), pages 722-733.
    19. Kaur, Jasleen & Ferrara, Emilio & Menczer, Filippo & Flammini, Alessandro & Radicchi, Filippo, 2015. "Quality versus quantity in scientific impact," Journal of Informetrics, Elsevier, vol. 9(4), pages 800-808.

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