Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/24858
Title: An analysis of retracted papers in Computer Science
Authors: Shepperd, M
Yousefi, L
Keywords: citation analysis;systematic reviews;computer and information sciences;meta-analysis;scientific misconduct;archives;database searching;cellular neuroscience
Issue Date: 9-May-2023
Citation: Shepperd,M. and Yousefi, L. (2023) 'An analysis of retracted papers in Computer Science', 18 (5), e0285383, pp. 1-17. doi: 10.1371/journal.pone.0285383.
Abstract: Copyright: © 2023 Shepperd, Yousefi. Context: The retraction of research papers, for whatever reason, is a growing phenomenon. However, although retracted paper information is publicly available via publishers, it is somewhat distributed and inconsistent. Objective: The aim is to assess: (i) the extent and nature of retracted research in Computer Science (CS) (ii) the post-retraction citation behaviour of retracted works and (iii) the potential impact upon systematic reviews and mapping studies. Method: We analyse the Retraction Watch database and take citation information from the Web of Science and Google scholar. Results: We find that of the 33,955 entries in the Retraction watch database (16 May 2022), 2,816 are classified as CS, i.e., ≈ 8%. For CS, 56% of retracted papers provide little or no information as to the reasons. This contrasts with 26% for other disciplines. There is also some disparity between different publishers, a tendency for multiple versions of a retracted paper to be available beyond the Version of Record (VoR), and for new citations long after a paper is officially retracted (median = 3; maximum = 18). Systematic reviews are also impacted with ≈ 30% of the retracted papers having one or more citations from a review. Conclusions: Unfortunately, retraction seems to be a sufficiently common outcome for a scientific paper that we as a research community need to take it more seriously, e.g., standardising procedures and taxonomies across publishers and the provision of appropriate research tools. Finally, we recommend particular caution when undertaking secondary analyses and meta-analyses which are at risk of becoming contaminated by these problem primary studies.
Description: Data Availability: The complete raw data cannot be shared publicly because of a data usage agreement with Retraction Watch that prohibits publishing more than 2% of the data set. This requirement arises because, in order to fund Retraction Watch’s continued operations, given that their initial grants have ended, they are licensing their data to commercial entities. Therefore researchers will need to approach Retraction Watch directly (retractionwatch.org) to obtain the same data set. We have placed our relevant code for this study in the Zenodo repository (https://doi.org/10.5281/zenodo.6634462).
URI: https://bura.brunel.ac.uk/handle/2438/24858
DOI: https://doi.org/10.1371/journal.pone.0285383
Other Identifiers: ORCID iDs: Martin Shepperd https://orcid.org/0000-0003-1874-6145; Leila Yousefi https://orcid.org/0000-0003-1952-0674.
e0285383
Appears in Collections:Dept of Computer Science Research Papers
Dept of Life Sciences Research Papers

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