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Comparison of different mathematical functions for the analysis of citation distribution of papers of individual authors

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  • Sangwal, Keshra

Abstract

The citation distribution of papers of selected individual authors was analyzed using five mathematical functions: power-law, stretched exponential, logarithmic, binomial and Langmuir-type. The former two functions have previously been proposed in the literature whereas the remaining three are novel and are derived following the concepts of growth kinetics of crystals in the presence of additives which act as inhibitors of growth. Analysis of the data of citation distribution of papers of the authors revealed that the value of the goodness-of-the-fit parameter R2 was the highest for the empirical binomial relation, it was high and comparable for stretched exponential and Langmuir-type functions, relatively low for power law but it was the lowest for the logarithmic function. In the Langmuir-type function a parameter K, defined as Langmuir constant, characterizing the citation behavior of the authors has been identified. Based on the Langmuir-type function an expression for cumulative citations L relating the extrapolated value of citations l0 corresponding to rank n=0 for an author and his/her constant K and the number N of paper receiving citation l≥1 is also proposed.

Suggested Citation

  • Sangwal, Keshra, 2013. "Comparison of different mathematical functions for the analysis of citation distribution of papers of individual authors," Journal of Informetrics, Elsevier, vol. 7(1), pages 36-49.
    • Handle: RePEc:eee:infome:v:7:y:2013:i:1:p:36-49
    DOI: 10.1016/j.joi.2012.09.002
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    References listed on IDEAS

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    1. Sangwal, Keshra, 2013. "Citation and impact factor distributions of scientific journals published in individual countries," Journal of Informetrics, Elsevier, vol. 7(2), pages 487-504.
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    3. Sangwal, Keshra, 2014. "Distributions of citations of papers of individual authors publishing in different scientific disciplines: Application of Langmuir-type function," Journal of Informetrics, Elsevier, vol. 8(4), pages 972-984.

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