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Citations and certainty: a new interpretation of citation counts

Author

Listed:
  • Henry Small

    (SciTech Strategies, Inc.)

  • Kevin W. Boyack

    (SciTech Strategies, Inc.)

  • Richard Klavans

    (SciTech Strategies, Inc.)

Abstract

We report that the rate of hedging in citing sentences for biomedical papers is inversely related to the citations received by the papers as measured by the number of citances in citing papers. Hedging is often regarded as an expression of uncertainty in rhetorical studies of scientific text. Citing sentences, or citances, are retrieved from the PubMed Central database for papers having 10 or more citances, and the percentage of citances containing hedging words is plotted against the number of citances for the papers, which is closely related to the citation count. Hedging rates are computed separately for method and non-method papers, the latter being more frequently hedged. Rates of hedging are found to be higher for papers with fewer citances, suggesting that the certainty of scientific results is directly related to citation frequency. Similarly, early citations made soon after publication are more hedged than later citations. The implications of this finding for the interpretation of citation counts are discussed, and the directions for future research.

Suggested Citation

  • Henry Small & Kevin W. Boyack & Richard Klavans, 2019. "Citations and certainty: a new interpretation of citation counts," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(3), pages 1079-1092, March.
    • Handle: RePEc:spr:scient:v:118:y:2019:i:3:d:10.1007_s11192-019-03016-z
    DOI: 10.1007/s11192-019-03016-z
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    References listed on IDEAS

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    1. Richard Van Noorden & Brendan Maher & Regina Nuzzo, 2014. "The top 100 papers," Nature, Nature, vol. 514(7524), pages 550-553, October.
    2. Small, Henry, 2018. "Characterizing highly cited method and non-method papers using citation contexts: The role of uncertainty," Journal of Informetrics, Elsevier, vol. 12(2), pages 461-480.
    3. Boyack, Kevin W. & van Eck, Nees Jan & Colavizza, Giovanni & Waltman, Ludo, 2018. "Characterizing in-text citations in scientific articles: A large-scale analysis," Journal of Informetrics, Elsevier, vol. 12(1), pages 59-73.
    4. Small, Henry & Tseng, Hung & Patek, Mike, 2017. "Discovering discoveries: Identifying biomedical discoveries using citation contexts," Journal of Informetrics, Elsevier, vol. 11(1), pages 46-62.
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    Cited by:

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    2. Lutz Bornmann & K. Brad Wray & Robin Haunschild, 2020. "Citation concept analysis (CCA): a new form of citation analysis revealing the usefulness of concepts for other researchers illustrated by exemplary case studies including classic books by Thomas S. K," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(2), pages 1051-1074, February.

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