Uncited papers in the structure of scientific communication

Yurij L. Katchanov, Yulia V. Markova and Natalia A. Shmatko

Journal of Informetrics, 2023, vol. 17, issue 2

Abstract: The paper presents an in-depth study of uncited papers. For that, we explore the documents indexed in the INSPIRE database from 1970 to 2015. Uncited articles represent a complex bibliometric environment in which references are generated. The reference lists of uncited papers form a dynamic system partially responsible for the redistribution of scientific impact. Our task is to quantify the detailed structure of citations and references directly in terms of quantiles. We also study the entropy and the statistical complexity measure of references and citations of papers’ quantiles. We introduce a theoretical framework in which citation distribution is considered an asymptotic distribution of the largest values in a sequence of independent identically distributed random variables. We show that this asymptotic distribution is the generalized extreme-value distribution. Furthermore, we empirically demonstrate that the asymptotic behavior of citation distribution is close to (but not quite) the generalized extreme-value distribution.

Keywords: Bibliometrics; Citation analysis; INSPIRE; Uncited papers; Uncitness (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:infome:v:17:y:2023:i:2:s1751157723000160

DOI: 10.1016/j.joi.2023.101391

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