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Global retractions due to randomly generated content: Characterization and trends

Author

Listed:
  • Fang Lei

    (Sichuan University)

  • Liang Du

    (Sichuan University
    Sichuan University
    Sichuan University)

  • Min Dong

    (Sichuan University)

  • Xuemei Liu

    (Sichuan University)

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

Suggested Citation

  • Fang Lei & Liang Du & Min Dong & Xuemei Liu, 2024. "Global retractions due to randomly generated content: Characterization and trends," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(12), pages 7943-7958, December.
    • Handle: RePEc:spr:scient:v:129:y:2024:i:12:d:10.1007_s11192-024-05172-3
    DOI: 10.1007/s11192-024-05172-3
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