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The mismeasure of science: Citation analysis

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  • Michael H. MacRoberts
  • Barbara R. MacRoberts

Abstract

For several decades we, among others, have criticized the use of citations for evaluative purposes. Although these criticisms have been noted, they have been largely brushed aside or ignored, not addressed head on. This may be for a number of reasons, but we believe the main one is that these criticisms undermine the desire to have an easy “scientific†—that is, quantitative—method of evaluation. Consequently, we continue and update our criticism of the use of citations for evaluation.

Suggested Citation

  • Michael H. MacRoberts & Barbara R. MacRoberts, 2018. "The mismeasure of science: Citation analysis," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 69(3), pages 474-482, March.
  • Handle: RePEc:bla:jinfst:v:69:y:2018:i:3:p:474-482
    DOI: 10.1002/asi.23970
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    Citations

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    Cited by:

    1. 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.
    2. Yu-Wei Chang & Dar-Zen Chen & Mu-Hsuan Huang, 2021. "Do extraordinary science and technology scientists balance their publishing and patenting activities?," PLOS ONE, Public Library of Science, vol. 16(11), pages 1-20, November.
    3. Alonso Rodríguez-Navarro & Ricardo Brito, 2019. "Probability and expected frequency of breakthroughs: basis and use of a robust method of research assessment," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 213-235, April.
    4. Andrey Lovakov & Elena Agadullina, 2019. "Bibliometric analysis of publications from post-Soviet countries in psychological journals in 1992–2017," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 1157-1171, May.
    5. Mingkun Wei & Abdolreza Noroozi Chakoli, 2020. "Evaluating the relationship between the academic and social impact of open access books based on citation behaviors and social media attention," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2401-2420, December.
    6. Faiza Qayyum & Muhammad Tanvir Afzal, 2019. "Identification of important citations by exploiting research articles’ metadata and cue-terms from content," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(1), pages 21-43, January.
    7. Brito, Ricardo & Navarro, Alonso Rodríguez, 2021. "The inconsistency of h-index: A mathematical analysis," Journal of Informetrics, Elsevier, vol. 15(1).
    8. Steffen Lemke & Athanasios Mazarakis & Isabella Peters, 2021. "Conjoint analysis of researchers' hidden preferences for bibliometrics, altmetrics, and usage metrics," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(6), pages 777-792, June.
    9. Lyu, Haihua & Bu, Yi & Zhao, Zhenyue & Zhang, Jiarong & Li, Jiang, 2022. "Citation bias in measuring knowledge flow: Evidence from the web of science at the discipline level," Journal of Informetrics, Elsevier, vol. 16(4).
    10. Lawrence Smolinsky & Daniel S. Sage & Aaron J. Lercher & Aaron Cao, 2021. "Citations versus expert opinions: citation analysis of featured reviews of the American Mathematical Society," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 3853-3870, May.
    11. Zheng Xie & Yanwu Li & Zhemin Li, 2020. "Assessing and predicting the quality of research master’s theses: an application of scientometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 953-972, August.
    12. Abramo, Giovanni, 2018. "Revisiting the scientometric conceptualization of impact and its measurement," Journal of Informetrics, Elsevier, vol. 12(3), pages 590-597.

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