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Comparison of bibliometric measures for assessing relative importance of researchers

Author

Listed:
  • Rok Blagus

    (University of Ljubljana)

  • Brane L. Leskošek

    (University of Ljubljana)

  • Janez Stare

    (University of Ljubljana)

Abstract

Quantitative evaluation of citation data to support funding decisions has become widespread. For this purpose there exist many measures (indices) and while their properties were well studied there is little comprehensive experimental comparison of the ranking lists obtained when using different methods. A further problem of the existing studies is that lack of available data about net citations prevents researchers from studying the effect of measuring scientific impact by using net citations (all citations minus self-citations). In this paper we use simulated data to study factors that could potentially influence the degree of agreement between the rankings obtained when using different indices with the emphasis given to the comparison of the number of net citations per author to other more established indices. We observe that the researchers publishing papers with a large number of co-authors are systematically ranked higher when using h-index or total citations (TC) instead of the number of citations per author (TCA), that the researchers who publish a small proportion of papers which receive many citations while the rest of their papers receive only few citations are systematically ranked higher when using TCA or TC instead of h-index, and that the authors who have lower proportion of self-citations are ranked higher when considering indices which include the number of net citations in comparison with indices considering only the total citation count. Results are verified and illustrated also by analyzing a large dataset from the field of medical science in Slovenia for the period 1986–2007.

Suggested Citation

  • Rok Blagus & Brane L. Leskošek & Janez Stare, 2015. "Comparison of bibliometric measures for assessing relative importance of researchers," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1743-1762, December.
    • Handle: RePEc:spr:scient:v:105:y:2015:i:3:d:10.1007_s11192-015-1622-6
    DOI: 10.1007/s11192-015-1622-6
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    References listed on IDEAS

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    1. Bornmann, Lutz & Mutz, Rüdiger & Hug, Sven E. & Daniel, Hans-Dieter, 2011. "A multilevel meta-analysis of studies reporting correlations between the h index and 37 different h index variants," Journal of Informetrics, Elsevier, vol. 5(3), pages 346-359.
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    2. Yufei Wang & Mangirdas Morkūnas & Jinzhao Wei, 2024. "Mapping the Landscape of Climate-Smart Agriculture and Food Loss: A Bibliometric and Bibliographic Analysis," Sustainability, MDPI, vol. 16(17), pages 1-24, September.
    3. Boris Forthmann & Mark Leveling & Yixiao Dong & Denis Dumas, 2020. "Investigating the quantity–quality relationship in scientific creativity: an empirical examination of expected residual variance and the tilted funnel hypothesis," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 2497-2518, September.
    4. Gordana Budimir & Sophia Rahimeh & Sameh Tamimi & Primož Južnič, 2021. "Comparison of self-citation patterns in WoS and Scopus databases based on national scientific production in Slovenia (1996–2020)," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(3), pages 2249-2267, March.
    5. 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.

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