ARTIFICIAL INTELLIGENCE IN QUALITATIVE RESEARCH: BIBLIOMETRIC ANALYSIS OF SCIENTIFIC PRODUCTION INDEXED IN SCOPUS
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https://orcid.org/0000-0002-5399-2766
Kevin Arnaldo Mejía Rivera
https://orcid.org/0000-0002-8941-8168
Abstract
The use of Artificial Intelligence (AI) in research has shown a growing trend in recent years, gaining significant attention from the scientific community compared to other techniques and software for information analysis. Objective to conduct an analysis of the main trends in the use of AI in qualitative research to characterize how AI is being employed in such scientific production. Methods involved a bibliometric analysis of scientific articles indexed in Scopus, using the VosViewer tool, followed by a conventional analysis of data grouped by type, volume of articles, citations, and their respective dating. Results identified four clusters; the first one concentrates 161 occurrences and a score of 572 in its relationship strength. Meanwhile, the second cluster recorded 144 occurrences and a score of 1004 in its relationship strength. Clusters 3 and 4 present lower relationship strength scores. Cluster 1 stands out because it presents the highest number of occurrences linked to the use of AI as the methodology used in the analyzed research. Characterization shows that research oriented towards knowledge production (pure research) surpasses research with an innovation component, representing only one-third of the total. The citation volume of the former also exceeds that of the latter. Additionally, it was observed that the fields of Computer Science and Medicine are the most prominent in this topic. Conclusions AI applied to qualitative research constitutes an increasingly common tool. Three key factors stand out in the use of AI in qualitative research: as a strategy to automate decision-making, to enhance human action, and to investigate as an effect of external factors.
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