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Modelling citation age data: Simple graphical methods from reliability theory

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  • Quentin L. Burrell

Abstract

Certain similarities between the types of data reported in retrospective citation analyses and lifetime/survival/reliability models are noted. Graphical techniques much used in reliability analyses are exploited to throw further light on observed citation age distributions and these are then compared and contrasted with previously reported studies. These simple techniques allow systematic departures of empirical data from assumed theoretical models to be highlighted and the models to be compared.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:scient:v:55:y:2002:i:2:d:10.1023_a:1019671808921
    DOI: 10.1023/A:1019671808921
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    References listed on IDEAS

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    1. Quentin L. Burrel, 2001. "Stochastic modelling of the first-citation distribution," Scientometrics, Springer;Akadémiai Kiadó, vol. 52(1), pages 3-12, September.
    2. 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.
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    Cited by:

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    2. Weimao Ke, 2013. "A fitness model for scholarly impact analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(3), pages 981-998, March.
    3. Wolfgang Glänzel, 2004. "Towards a model for diachronous and synchronous citation analyses," Scientometrics, Springer;Akadémiai Kiadó, vol. 60(3), pages 511-522, August.
    4. 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.
    5. Anthony G. Stacey, 2021. "Ages of cited references and growth of scientific knowledge: an explication of the gamma distribution in business and management disciplines," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 619-640, January.
    6. Sarabia, José María, 2008. "A general definition of the Leimkuhler curve," Journal of Informetrics, Elsevier, vol. 2(2), pages 156-163.
    7. Giovanni Abramo & Ciriaco Andrea D’Angelo & Tindaro Cicero, 2012. "What is the appropriate length of the publication period over which to assess research performance?," Scientometrics, Springer;Akadémiai Kiadó, vol. 93(3), pages 1005-1017, December.
    8. Saralees Nadarajah & Samuel Kotz, 2007. "Models for citation behavior," Scientometrics, Springer;Akadémiai Kiadó, vol. 72(2), pages 291-305, August.
    9. Balakrishnan, N. & Sarabia, José María & Kolev, Nikolai, 2010. "A simple relation between the Leimkuhler curve and the mean residual life," Journal of Informetrics, Elsevier, vol. 4(4), pages 602-607.
    10. Emil Hudomalj & Gaj Vidmar, 2003. "OLAP and bibliographic databases," Scientometrics, Springer;Akadémiai Kiadó, vol. 58(3), pages 609-622, November.
    11. Yin, Yian & Wang, Dashun, 2017. "The time dimension of science: Connecting the past to the future," Journal of Informetrics, Elsevier, vol. 11(2), pages 608-621.
    12. Glänzel Wolfgang & Thijs Bart & Schlemmer Balázs, 2004. "A bibliometric approach to the role of author self-citations in scientific communication," Scientometrics, Springer;Akadémiai Kiadó, vol. 59(1), pages 63-77, January.

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