Empirical demonstration of the Matthew effect in scientific research careers

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

Journal of Informetrics, 2023, vol. 17, issue 4

Abstract: The Matthew effect qualitatively describes the social phenomenon that the impact and recognition of well-known scientists for their new accomplishments are relatively overpriced by the scientific community when compared to the similar output of researchers without fame or status. We quantify the manifestation of this phenomenon in scientific research careers. For this purpose, using a mixed survey-plus-bibliometrics method, we assembled a dataset containing detailed career information on scientists in the field of chemistry. The mathematical model of the Matthew effect in scientific research careers proposed in this paper identifies career distribution as the generalized extreme value distribution with the shape parameter q=0.5. This result is in good agreement with the obtained data: the empirical distribution of scientific careers can be approximated by the generalized extreme value distribution with q=0.423. We also find that the distribution of starting positions of social trajectories of scientists fits by the Pareto distribution. Our analysis deepens scientific insight into the emergence of the Matthew effect in scientific careers and its relationship to the distribution of citations and citation entropy.

Keywords: Citation analysis; Matthew effect; Survey-plus-bibliometrics; Scientific career; Scientometrics (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:infome:v:17:y:2023:i:4:s1751157723000901

DOI: 10.1016/j.joi.2023.101465

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