 Hidden scales in statistics of citation indicatorsAndrey M. Tokmachev Journal of Informetrics, 2023, vol. 17, issue 1 Abstract: Scholarly citations – widely seen as tangible measures of the impact and significance of academic papers – guide critical decisions by research administrators and policy makers. The citation distributions form characteristic patterns that can be revealed by big-data analysis. However, the citation dynamics varies significantly among subject areas, countries etc. The problem is how to quantify those differences, separate global and local citation characteristics. Here, we carry out an extensive analysis of the power-law relationship between the total citation count and the h-index to detect a functional dependence among its parameters for different science domains. The results demonstrate that the statistical structure of the citation indicators admits representation by a global scale and a set of local exponents. The scale parameters are evaluated for different research actors – individual researchers and entire countries – employing subject- and affiliation-based divisions of science into domains. The results can inform research assessment and classification into subject areas; the proposed divide-and-conquer approach can be applied to hidden scales in other power-law systems. Keywords: Citation analysis; Power law; h-index; Scale; Discipline bias; Scopus (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:infome:v:17:y:2023:i:1:s1751157722001092 DOI: 10.1016/j.joi.2022.101356 Access Statistics for this article Journal of Informetrics is currently edited by Leo Egghe More articles in Journal of Informetrics from Elsevier |
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