TEXT MINING AND CLUSTERING IN BIBLIOMETRIC STUDIES: THE SCIENTIFIC MAPPING OF THESES AND DISSERTATIONS OF A GRADUATE PROGRAM
DOI:
https://doi.org/10.48090/ciki.v1i1.1036Keywords:
Mining texts, Bibliometry, Scientific mapping, VOSviewer®, Orange®Abstract
Bibliometric studies have the particularity of analyzing the performance of a research field/area. The present study, following this premise, will map the works of a Postgraduate program at a Brazilian Federal University. For this purpose, text mining and clustering techniques are used to analyze 609 works, including theses and dissertations. The use of text mining techniques and visualization of similarities provided the indication of groupings of knowledge areas. The similarity analysis indicates the little interaction between the fields of knowledge, characterizing the existence of “conceptual islands”. This result may have been impacted by the way the data was extracted in the similarity analysis. The analysis also made it possible to verify which themes arouse greater interest in the program in relation to the research being carried out.
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