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Theory and experimentation on the most-recent-reference distribution

Author

Listed:
  • Leo Egghe

    (Universitaire Campus)

  • I. K. R. Ravichandra Rao

    (ISI)

Abstract

The cumulative distribution of the age of the most-recent-reference distribution is the “dual” variant of the first-citation distribution. The latter has been modelled in previous publications of different authors but the former one has not. This paper studies a model of this cumulative most-recent-reference distribution which is different from the first-citation distribution. This model is checked on JASIS and JACS data, with success. The model involves the determination of 3 parameters and is a transformation of the lognormal distribution. However we also show that the first-citation model (involving only 2 parameters and which is easier to handle), developed in an earlier paper, gives enough freedom to give close fits to the most-recent-reference data as well.

Suggested Citation

  • Leo Egghe & I. K. R. Ravichandra Rao, 2002. "Theory and experimentation on the most-recent-reference distribution," Scientometrics, Springer;Akadémiai Kiadó, vol. 53(3), pages 371-387, March.
  • Handle: RePEc:spr:scient:v:53:y:2002:i:3:d:10.1023_a:1014825113328
    DOI: 10.1023/A:1014825113328
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    References listed on IDEAS

    as
    1. Leo Egghe & Ronald Rousseau, 2000. "The influence of publication delays on the observed aging distribution of scientific literature," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 51(2), pages 158-165.
    2. Leo Egghe, 2000. "A Heuristic Study of the First-Citation Distribution," Scientometrics, Springer;Akadémiai Kiadó, vol. 48(3), pages 345-359, July.
    3. N. Gilbert, 1997. "A Simulation of the Structure of Academic Science," Sociological Research Online, , vol. 2(2), pages 91-105, June.
    4. H. S. Sichel, 1992. "Note on a strongly unimodal bibliometric size frequency distribution," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 43(4), pages 299-303, May.
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    Cited by:

    1. Vîiu, Gabriel-Alexandru, 2018. "The lognormal distribution explains the remarkable pattern documented by characteristic scores and scales in scientometrics," Journal of Informetrics, Elsevier, vol. 12(2), pages 401-415.
    2. Fred Y. Ye, 2007. "A quantitative relationship between per capita GDP and scientometric criteria," Scientometrics, Springer;Akadémiai Kiadó, vol. 71(3), pages 407-413, June.
    3. Pablo Dorta-González & Emilio Gómez-Déniz, 2022. "Modeling the obsolescence of research literature in disciplinary journals through the age of their cited references," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(6), pages 2901-2931, June.
    4. Wang, Xianwen & Wang, Zhi & Mao, Wenli & Liu, Chen, 2014. "How far does scientific community look back?," Journal of Informetrics, Elsevier, vol. 8(3), pages 562-568.
    5. Saralees Nadarajah & Samuel Kotz, 2007. "Models for citation behavior," Scientometrics, Springer;Akadémiai Kiadó, vol. 72(2), pages 291-305, August.
    6. Quentin L. Burrell, 2002. "Modelling citation age data: Simple graphical methods from reliability theory," Scientometrics, Springer;Akadémiai Kiadó, vol. 55(2), pages 273-285, August.

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