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Measuring concentration within and co-concentration between informetric distributions: An empirical study

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  • Quentin L. Burrell

    (Isle of Man International Business School)

Abstract

Summary There is a well-established literature on the use of concentration measures in informetrics. However, these works have usually been devoted to measures of concentration within a productivity distribution. In a pair of recent papers the author introduced two new measures, both based on the Gini ratio, for measuring the similarity of concentration of productivity between two different informetric distributions. The first of these was derived from Dagum's notion of relative economic affluence; the second - in some ways analogous to the correlation coefficient - is completely new. The purpose of this study is to develop a purely empirical approach to comparative studies of concentration between informetric data sets using both within and between measures thereby greatly extending the original study which considered just two data sets for purposes of illustration of the methods of calculation of the measures.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:scient:v:68:y:2006:i:3:d:10.1007_s11192-006-0122-0
    DOI: 10.1007/s11192-006-0122-0
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    Cited by:

    1. Quentin L. Burrell, 2007. "Time-dependent aspects of co-concentration in informetrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 73(2), pages 161-174, November.
    2. 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.
    3. 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.
    4. Saeed-Ul Hassan & Peter Haddawy, 2015. "Analyzing knowledge flows of scientific literature through semantic links: a case study in the field of energy," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(1), pages 33-46, April.

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