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A bibliometric analysis of plagiarism and self-plagiarism through Déjà vu

Abstract

Plagiarism is one of the most important current debates among scientific stakeholders. A separate but related issue is the use of authors’ own ideas in different papers (i.e., self-plagiarism). Opinions on this issue are mixed, and there is a lack of consensus. Our goal was to gain deeper insight into plagiarism and self-plagiarism through a citation analysis of documents involved in these situations. The Déjà vu database, which comprises around 80,000 duplicate records, was used to select 247 pairs of documents that had been examined by curators on a full text basis following a stringent protocol. We then used the Scopus database to perform a citation analysis of the selected documents. For each document pair, we used specific bibliometric indicators, such as the number of authors, full text similarity, journal impact factor, the Eigenfactor, and article influence. Our results confirm that cases of plagiarism are published in journals with lower visibility and thus tend to receive fewer citations. Moreover, full text similarity was significantly higher in cases of plagiarism than in cases of self-plagiarism. Among pairs of documents with shared authors, duplicates not citing the original document showed higher full text similarity than those citing the original document, and also showed greater overlap in the references cited in the two documents.

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Acknowledgments

We are grateful to Grant Lewison, Juan Gorraiz, Juan M. García Ruiz, and Javier Ruiz-Castillo for their comments on an earlier version of the manuscript, although any errors are our own and should not tarnish the reputations of these esteemed persons. We also wish to thank the two “anonymous” reviewers for their comments and suggestions.

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Correspondence to Antonio García-Romero.

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García-Romero, A., Estrada-Lorenzo, J.M. A bibliometric analysis of plagiarism and self-plagiarism through Déjà vu. Scientometrics 101, 381–396 (2014). https://doi.org/10.1007/s11192-014-1387-3

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  • DOI: https://doi.org/10.1007/s11192-014-1387-3

Keywords

  • Plagiarism
  • Duplicate publications
  • Déjà vu
  • Citation analysis