Déjà vu--a study of duplicate citations in Medline.
BACKGROUND
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.


BACKGROUND
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
Errami
Mounir
M
UT Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas TX 75390-9185, USA.
Hicks
Justin M
JM
Fisher
Wayne
W
Trusty
David
D
Wren
Jonathan D
JD
Long
Tara C
TC
Garner
Harold R
HR
D015706:Bibliometrics; D016239:MEDLINE / Q000706:statistics & numerical data*; D046650:Medical Subject Headings; D009323:Natural Language Processing; D010506:Periodicals as Topic / Q000706:statistics & numerical data*; D015714:Plagiarism; D012660:Semantics; D018875:Vocabulary, Controlled