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Power laws in citation distributions: Evidence from Scopus

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  • Michał Brzeziński

    ()
    (Faculty of Economic Sciences, University of Warsaw)

Abstract

Modeling distributions of citations to scientific papers is crucial for understanding how science develops. However, there is a considerable empirical controversy on which statistical model fits the citation distributions best. This paper is concerned with rigorous empirical detection of power-law behaviour in the distribution of citations received by the most highly cited scientific papers. We have used a large, novel data set on citations to scientific papers published between 1998 and 2002 drawn from Scopus. The power-law model is compared with a number of alternative models using a likelihood ratio test. We have found that the power-law hypothesis is rejected for around half of the Scopus fields of science. For these fields of science, the Yule, power-law with exponential cut-off and log-normal distributions seem to fit the data better than the pure power-law model. On the other hand, when the power-law hypothesis is not rejected, it is usually empirically indistinguishable from most of the alternative models.

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File URL: http://www.wne.uw.edu.pl/inf/wyd/WP/WNE_WP122.pdf
File Function: First version, 2014
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Bibliographic Info

Paper provided by Faculty of Economic Sciences, University of Warsaw in its series Working Papers with number 2014-05.

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Length: 15 pages
Date of creation: 2014
Date of revision:
Handle: RePEc:war:wpaper:2014-05

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Related research

Keywords: power law; Pareto model; citation distribution; bibliometrics; scientometrics; Scopus; model selection;

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  1. Xavier Gabaix, 2009. "Power Laws in Economics and Finance," Annual Review of Economics, Annual Reviews, vol. 1(1), pages 255-294, 05.
  2. S. Redner, 1998. "How popular is your paper? An empirical study of the citation distribution," The European Physical Journal B - Condensed Matter and Complex Systems, Springer, vol. 4(2), pages 131-134, July.
  3. López-Illescas, Carmen & de Moya-Anegón, Félix & Moed, Henk F., 2008. "Coverage and citation impact of oncological journals in the Web of Science and Scopus," Journal of Informetrics, Elsevier, vol. 2(4), pages 304-316.
  4. Aghaei Chadegani, Arezoo & Salehi, Hadi & Md Yunus, Melor & Farhadi, Hadi & Fooladi, Masood & Farhadi, Maryam & Ale Ebrahim, Nader, 2013. "A Comparison between Two Main Academic Literature Collections: Web of Science and Scopus Databases," MPRA Paper 46898, University Library of Munich, Germany, revised 18 Mar 2013.
  5. Pedro Albarrán & Juan A. Crespo & Ignacio Ortuño & Javier Ruiz-Castillo, 2010. "The skewness of science in 219 sub-fields and a number of aggregates," Economics Working Papers we1038, Universidad Carlos III, Departamento de Economía.
  6. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-33, March.
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