Global retractions due to randomly generated content: Characterization and trends

Fang Lei, Liang Du, Min Dong and Xuemei Liu ()
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Fang Lei: Sichuan University
Liang Du: Sichuan University
Min Dong: Sichuan University
Xuemei Liu: Sichuan University

Scientometrics, 2024, vol. 129, issue 12, No 21, 7943-7958

Abstract: Abstract The aim of the study was to characterize retractions due to randomly generated content. A cross-sectional study was performed, using Retraction Watch database, Journal Citation Reports, Scopus, and journal official websites as data sources. Papers retracted up to 28 May 2024 with reasons related to randomly generated content were included. A total of 3540 retractions were identified. The first retraction was conducted in 2010, and the number of retractions per year escalated from 3 in 2010 to 2302 in 2023. The delay in retraction for papers published between 2020 and 2023 was shorter than that for those published prior to 2020 [2248 (1293, 2687) days vs. 387 (335, 516) days, P

Keywords: Retraction; Randomly generated content; Publication ethics; Artificial intelligence; Bibliometric analysis (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11192-024-05172-3

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