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An empirical approach based on quantile regression for estimating citation ageing

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  • Galiani, Sebastian
  • Gálvez, Ramiro H.

Abstract

An aspect of citation behavior, which has received longstanding attention in research, is how articles’ received citations evolve as time passes since their publication (i.e., citation ageing). Citation ageing has been studied mainly by the formulation and fit of mathematical models of diverse complexity. Commonly, these models restrict the shape of citation ageing functions and explicitly take into account factors known to influence citation ageing. An alternative—and less studied—approach is to estimate citation ageing functions using data-driven strategies. However, research following the latter approach has not been consistent in taking into account those factors known to influence citation ageing. In this article, we propose a model-free approach for estimating citation ageing functions which combines quantile regression with a non-parametric specification able to capture citation inflation. The proposed strategy allows taking into account field of research effects, impact level effects, citation inflation effects and skewness in the distribution of cites effects. To test our methodology, we collected a large dataset consisting of more than five million citations to 59,707 research articles spanning 12 dissimilar fields of research and, with this data in hand, tested the proposed strategy.

Suggested Citation

  • Galiani, Sebastian & Gálvez, Ramiro H., 2019. "An empirical approach based on quantile regression for estimating citation ageing," Journal of Informetrics, Elsevier, vol. 13(2), pages 738-750.
    • Handle: RePEc:eee:infome:v:13:y:2019:i:2:p:738-750
    DOI: 10.1016/j.joi.2019.03.014
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    Citations

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    Cited by:

    1. María Victoria Anauati & Sebastian Galiani & Ramiro H. Gálvez, 2020. "Differences In Citation Patterns Across Journal Tiers: The Case Of Economics," Economic Inquiry, Western Economic Association International, vol. 58(3), pages 1217-1232, July.
    2. Istvan-Szilard Szilagyi & Gregor A. Schittek & Christoph Klivinyi & Holger Simonis & Torsten Ulrich & Helmar Bornemann-Cimenti, 2022. "Citation of retracted research: a case-controlled, ten-year follow-up scientometric analysis of Scott S. Reuben’s malpractice," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(5), pages 2611-2620, May.
    3. Rose, Michael E. & Opolot, Daniel C. & Georg, Co-Pierre, 2022. "Discussants," Research Policy, Elsevier, vol. 51(10).
    4. Yu, Dejian & Pan, Tianxing, 2021. "Tracing the main path of interdisciplinary research considering citation preference: A case from blockchain domain," Journal of Informetrics, Elsevier, vol. 15(2).

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