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Citation Metrics: A Primer on How (Not) to Normalize

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  • John P A Ioannidis
  • Kevin Boyack
  • Paul F Wouters

Abstract

Citation metrics are increasingly used to appraise published research. One challenge is whether and how to normalize these metrics to account for differences across scientific fields, age (year of publication), type of document, database coverage, and other factors. We discuss the pros and cons for normalizations using different approaches. Additional challenges emerge when citation metrics need to be combined across multiple papers to appraise the corpus of scientists, institutions, journals, or countries, as well as when trying to attribute credit in multiauthored papers. Different citation metrics may offer complementary insights, but one should carefully consider the assumptions that underlie their calculation.Citation metrics are very influential and their normalization is a contentious issue. Each normalization approach has advantages and disadvantages that need to be understood for proper use of these metrics.

Suggested Citation

  • John P A Ioannidis & Kevin Boyack & Paul F Wouters, 2016. "Citation Metrics: A Primer on How (Not) to Normalize," PLOS Biology, Public Library of Science, vol. 14(9), pages 1-7, September.
    • Handle: RePEc:plo:pbio00:1002542
    DOI: 10.1371/journal.pbio.1002542
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    Cited by:

    1. Bornmann, Lutz & Haunschild, Robin & Mutz, Rüdiger, 2020. "Should citations be field-normalized in evaluative bibliometrics? An empirical analysis based on propensity score matching," Journal of Informetrics, Elsevier, vol. 14(4).
    2. Wang, Jiang-Pan & Guo, Qiang & Zhou, Lei & Liu, Jian-Guo, 2019. "Dynamic credit allocation for researchers," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 520(C), pages 208-216.
    3. Cano-Marin, Enrique & Mora-Cantallops, Marçal & Sánchez-Alonso, Salvador, 2023. "Twitter as a predictive system: A systematic literature review," Journal of Business Research, Elsevier, vol. 157(C).
    4. Antonin Mac'e, 2017. "The Limits of Citation Counts," Papers 1711.02695, arXiv.org, revised Sep 2023.
    5. Rodríguez-Navarro, Alonso & Brito, Ricardo, 2018. "Double rank analysis for research assessment," Journal of Informetrics, Elsevier, vol. 12(1), pages 31-41.
    6. Maziar Montazerian & Edgar Dutra Zanotto & Hellmut Eckert, 2020. "Prolificacy and visibility versus reputation in the hard sciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(1), pages 207-221, April.
    7. Dunaiski, Marcel & Geldenhuys, Jaco & Visser, Willem, 2019. "On the interplay between normalisation, bias, and performance of paper impact metrics," Journal of Informetrics, Elsevier, vol. 13(1), pages 270-290.
    8. Juan Miguel Campanario, 2018. "Are leaders really leading? Journals that are first in Web of Science subject categories in the context of their groups," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(1), pages 111-130, April.
    9. Robin Haunschild & Lutz Bornmann, 2022. "Relevance of document types in the scores’ calculation of a specific field-normalized indicator: Are the scores strongly dependent on or nearly independent of the document type handling?," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(8), pages 4419-4438, August.
    10. Maziar Montazerian & Edgar Dutra Zanotto & Hellmut Eckert, 2019. "A new parameter for (normalized) evaluation of H-index: countries as a case study," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(3), pages 1065-1078, March.
    11. Antonin Macé, 2023. "The Limits of Citation Counts," Working Papers halshs-01630095, HAL.
    12. Haunschild, Robin & Daniels, Angela D. & Bornmann, Lutz, 2022. "Scores of a specific field-normalized indicator calculated with different approaches of field-categorization: Are the scores different or similar?," Journal of Informetrics, Elsevier, vol. 16(1).
    13. Loet Leydesdorff & Paul Wouters & Lutz Bornmann, 2016. "Professional and citizen bibliometrics: complementarities and ambivalences in the development and use of indicators—a state-of-the-art report," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 2129-2150, December.
    14. Dag W. Aksnes & Liv Langfeldt & Paul Wouters, 2019. "Citations, Citation Indicators, and Research Quality: An Overview of Basic Concepts and Theories," SAGE Open, , vol. 9(1), pages 21582440198, February.
    15. Edgar D. Zanotto & Vinicius Carvalho, 2021. "Article age- and field-normalized tools to evaluate scientific impact and momentum," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 2865-2883, April.
    16. Clemens Blümel & Alexander Schniedermann, 2020. "Studying review articles in scientometrics and beyond: a research agenda," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 711-728, July.
    17. Lutz Bornmann & Richard Williams, 2020. "An evaluation of percentile measures of citation impact, and a proposal for making them better," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 1457-1478, August.

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