Déjà vu—A study of duplicate citations in Medline
BioinformaticsPublished 1 December 2007Open access
Mounir Errami, Justin M. Hicks, Wayne G. Fisher, David Trusty, Jonathan D. Wren, Tara C. Long
Citations95
SJR quartileQ1
SJR score2.45
SNIP1.47
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TL;DR
Using text similarity searches, a database of manually verified duplicate citations was created to study author publication behavior and found that 0.04% of the citations with no shared authors were highly similar and are thus potential cases of plagiarism.
Abstract
MOTIVATION: Duplicate publication impacts the quality of the scientific corpus, has been difficult to detect, and studies this far have been limited in scope and size. Using text similarity searches, we were able to identify signatures of duplicate citations among a body of abstracts. RESULTS: A sample of 62,213 Medline citations was examined and a database of manually verified duplicate citations was created to study author publication behavior. We found that 0.04% of the citations with no shared authors were highly similar and are thus potential cases of plagiarism. 1.35% with shared authors were sufficiently similar to be considered a duplicate. Extrapolating, this would correspond to 3500 and 117,500 duplicate citations in total, respectively. AVAILABILITY: eTBLAST, an automated citation matching tool, and Déjà vu, the duplicate citation database, are freely available at http://invention.swmed.edu/ and http://spore.swmed.edu/dejavu
Keywords
Social SciencesDecision Sciences
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