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Time-dependent aspects of co-concentration in informetrics

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  • Quentin L. Burrell

    (Isle of Man International Business School)

Abstract

It is a well-known empirical fact that when informetric processes are observed over an extending period of time, the entire shape of the distribution changes. In particular, it has been shown that concentration aspects change. In this paper the recently introduced co-concentration coefficient (C-CC) is investigated via simple stochastic models of informetric processes to investigate its time-dependence. It is shown that it is important to distinguish between situations where the zero-producers can be counted and those where they cannot. A previously published data set is used to illustrate how the empirical C-CC develops in time and the general features are compared with those derived from the theoretical model.

Suggested Citation

  • Quentin L. Burrell, 2007. "Time-dependent aspects of co-concentration in informetrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 73(2), pages 161-174, November.
    • Handle: RePEc:spr:scient:v:73:y:2007:i:2:d:10.1007_s11192-007-1688-x
    DOI: 10.1007/s11192-007-1688-x
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    References listed on IDEAS

    as
    1. Quentin L. Burrell, 2005. "Are “Sleeping Beauties” to be expected?," Scientometrics, Springer;Akadémiai Kiadó, vol. 65(3), pages 381-389, December.
    2. Quentin L. Burrell, 2003. "Predicting future citation behavior," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 54(5), pages 372-378, March.
    3. Dorfman, Robert, 1979. "A Formula for the Gini Coefficient," The Review of Economics and Statistics, MIT Press, vol. 61(1), pages 146-149, February.
    4. András Schubert & András Telcs, 1989. "Estimation of the publication potential in 50 U.S. states and in the District of Columbia based on the frequency distribution of scientific productivity," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 40(4), pages 291-297, July.
    5. Quentin L. Burrell, 2005. "The use of the generalized Waring process in modelling informetric data," Scientometrics, Springer;Akadémiai Kiadó, vol. 64(3), pages 247-270, August.
    6. Quentin L. Burrell, 2006. "Measuring concentration within and co-concentration between informetric distributions: An empirical study," Scientometrics, Springer;Akadémiai Kiadó, vol. 68(3), pages 441-456, September.
    7. H. S. Sichel, 1985. "A bibliometric distribution which really works," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 36(5), pages 314-321, September.
    8. Quentin L. Burrel, 2001. "Stochastic modelling of the first-citation distribution," Scientometrics, Springer;Akadémiai Kiadó, vol. 52(1), pages 3-12, September.
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    Cited by:

    1. Qiuju Zhou & Ronald Rousseau & Liying Yang & Ting Yue & Guoliang Yang, 2012. "A general framework for describing diversity within systems and similarity between systems with applications in informetrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 93(3), pages 787-812, December.

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