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Balance: a thermodynamic perspective

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  • Gangan Prathap

    (A P J Abdul Kalam Technological University)

Abstract

Balance (or evenness) as used in conventional approaches to measuring diversity needs careful definition. Nijssen et al. (Coenoses 13(1):33–38, 1998) used a mathematical approach to show that the Lorenz curve is an adequate representation of evenness and proposed that the Gini coefficient is a perfect indicator of balance. In this paper, we take an alternative thermodynamic perspective that leads to a very simple dimensionless measure of balance that ranges from 0 (perfect balance or evenness) to 1 (perfect unevenness or absolute concentration). It has the expected permutation invariance, scaling invariance, and replication invariance properties of a good evenness indicator and also has sensitivity to the transfer requirements (i.e. sensing the entropy changes correctly). It also has a naturalness property.

Suggested Citation

  • Gangan Prathap, 2019. "Balance: a thermodynamic perspective," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 247-255, April.
    • Handle: RePEc:spr:scient:v:119:y:2019:i:1:d:10.1007_s11192-019-03020-3
    DOI: 10.1007/s11192-019-03020-3
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    References listed on IDEAS

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    1. Ismael Rafols & Martin Meyer, 2010. "Diversity and network coherence as indicators of interdisciplinarity: case studies in bionanoscience," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(2), pages 263-287, February.
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    3. Ronald Rousseau, 2018. "The repeat rate: from Hirschman to Stirling," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(1), pages 645-653, July.
    4. Loet Leydesdorff, 2018. "Diversity and interdisciplinarity: how can one distinguish and recombine disparity, variety, and balance?," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 2113-2121, September.
    5. Andy Stirling, 2007. "A General Framework for Analysing Diversity in Science, Technology and Society," SPRU Working Paper Series 156, SPRU - Science Policy Research Unit, University of Sussex Business School.
    6. Leo Egghe, 2004. "The source-item coverage of the Lotka function," Scientometrics, Springer;Akadémiai Kiadó, vol. 61(1), pages 103-115, September.
    7. Gangan Prathap, 2014. "Quantity, quality, and consistency as bibliometric indicators," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(1), pages 214-214, January.
    8. 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.
    9. Loet Leydesdorff & Dieter Franz Kogler & Bowen Yan, 2017. "Mapping patent classifications: portfolio and statistical analysis, and the comparison of strengths and weaknesses," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1573-1591, September.
    10. Lin Zhang & Ronald Rousseau & Wolfgang Glänzel, 2016. "Diversity of references as an indicator of the interdisciplinarity of journals: Taking similarity between subject fields into account," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(5), pages 1257-1265, May.
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    Cited by:

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    2. Deming Lin & Tianhui Gong & Wenbin Liu & Martin Meyer, 2020. "An entropy-based measure for the evolution of h index research," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2283-2298, December.
    3. Gangan Prathap, 2023. "Letter to the Editor: Comments on the paper of Safón and Docampo: what are you reading? From core journals to trendy journals in the Library and Information Science (LIS) field," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(7), pages 4137-4142, July.

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