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A model for reference list length of scholarly articles

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  • Fatemeh Ghaffari

    (University of Massachusetts Amherst
    University of Massachusetts Amherst)

  • Mark C. Wilson

    (University of Massachusetts Amherst
    University of Massachusetts Amherst)

Abstract

We introduce and analyse a simple probabilistic model of article production and citation behavior that explicitly assumes that there is no decline in citability of a given article over time. It makes predictions about the number and age of items appearing in the reference list of an article. The latter topics have been studied before, but only in the context of data, and to our knowledge no models have been presented. We then perform large-scale analyses of reference list length for a variety of academic disciplines. The results show that our simple model cannot be rejected, and indeed fits the aggregated data on reference lists rather well. Over the last few decades, the relationship between total publications and mean reference list length is linear to a high level of accuracy. Although our model is clearly an oversimplification, it will likely prove useful for further modeling of the scholarly literature. Finally, we connect our work to the large literature on “aging” or “obsolescence” of scholarly publications, and argue that the importance of that area of research is no longer clear, while much of the existing literature is confused and confusing.

Suggested Citation

  • Fatemeh Ghaffari & Mark C. Wilson, 2023. "A model for reference list length of scholarly articles," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(9), pages 5335-5350, September.
  • Handle: RePEc:spr:scient:v:128:y:2023:i:9:d:10.1007_s11192-023-04780-9
    DOI: 10.1007/s11192-023-04780-9
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    References listed on IDEAS

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    1. Iñaki Ucar & Felipe López-Fernandino & Pablo Rodriguez-Ulibarri & Laura Sesma-Sanchez & Veronica Urrea-Micó & Joaquín Sevilla, 2014. "Growth in the number of references in engineering journal papers during the 1972–2013 period," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 1855-1864, March.
    2. 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.
    3. Werner Marx & Lutz Bornmann, 2016. "Change of perspective: bibliometrics from the point of view of cited references—a literature overview on approaches to the evaluation of cited references in bibliometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 1397-1415, November.
    4. V. Cano, 1989. "Citation behavior: Classification, utility, and location," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 40(4), pages 284-290, July.
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