A new model to identify the productivity of theses in terms of articles using co-word analysis

A thesis defense should be considered as not the end but the starting point for scientific communication flow. How many articles truly extend doctoral research? This article proposes a new model to automatically identify the productivity of theses in terms of article publications. We evaluate the use of the co-word analysis technique to establish relationships among 401 doctoral theses and 2,211 articles journal articles published by students in a graduate program at a Brazilian National Nuclear Research Institution (IPEN-CNEN/SP). To identify the relationship between a thesis and an article published by the same author, we used co-descriptor pairs from a controlled vocabulary. To validate the proposed model, a survey was applied to a random sample of theses authors (n = 128, response rate of 79%), thus establishing a minimum threshold of three coincident co-descriptors to identify the relationship between theses and articles. The agreement level between an author's opinion and the automatic method was 86.9%, with a sampling error of 7.36%, which indicates an acceptable level of accuracy. Differences between the related or nonrelated distributions of articles were also demonstrated, as was a reduction in the median lag time to publication and the supervisor's influence on student productivity.