Potential Predictibility of References in the Identification of Derivative Articles from Doctoral Theses

Mercedes Echeverria, David Stuart, Tobias Blanke

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

73 Downloads (Pure)

Abstract

This paper reports the results obtained on the predictability of references for the identification of derivative articles from doctoral theses, based on a sample of 68 medical theses and 334 articles published by the same theses authors. The study performs an analysis of the common references shared by theses and articles through a text similarity approach. A textual similarity comparison is carried out with the discursive sections of articles (Introduction,Methodology, Results and Discussion) based on the full-text of theses and articles. The results suggest that the Reference section has a high sensitivity to detect true positives cases and a low specificity to identify negative cases, corresponding to a high recall a low precision in the detection of derivative articles.
Original languageEnglish
Title of host publication10th International CALIBER 2015
Pages171-181
Publication statusPublished - 12 Mar 2015

Fingerprint

Dive into the research topics of 'Potential Predictibility of References in the Identification of Derivative Articles from Doctoral Theses'. Together they form a unique fingerprint.

Cite this