The rise of hyperprolific authors in computer science: characterization and implications

Edré Moreira (), Wagner Meira (), Marcos André Gonçalves () and Alberto H. F. Laender ()
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Edré Moreira: Universidade Federal de Minas Gerais
Wagner Meira: Universidade Federal de Minas Gerais
Marcos André Gonçalves: Universidade Federal de Minas Gerais
Alberto H. F. Laender: Universidade Federal de Minas Gerais

Scientometrics, 2023, vol. 128, issue 5, No 16, 2945-2974

Abstract: Abstract In this article we study and characterize the phenomenon of the hyperprolific authors, who are the most productive researchers according to a given repository in a specific period of time. Particularly, we are interested in investigating and characterizing a subset of such hyperprolific authors who present a sudden growth in the number of published articles and coauthors, as well as concentrate their publications in a few specific journals, what can be seen as an anomalous behavior. Using data collected from the DBLP repository and covering the last 10 years, we propose a set of discriminative dimensions (features) aimed at characterizing the behavior of hyperprolific authors, ultimately helping to identify anomalous ones. Moreover, using a strategy based on ranking aggregation to identify the most prominent anomalous authors, we demonstrate that the best dimensions to characterize such anomalous behaviors may vary significantly among authors, but it is possible to identify a clear subset of them who present such behavior. Our results show that the top-ranked (most anomalous) authors manifest a distinct behavior from the middle-ranked ones. Indeed, each one of the five most anomalous authors published more than 48 journal articles in 2021 while collaborating with more than 1,000 coauthors in their careers. Specifically, one of such authors published more than 140 articles in just a single journal.

Keywords: Scientific production; Publication growth; Hyperprolific authors; Computer science; DBLP (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11192-023-04676-8

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