Artificial intelligence: bibliometric analysis of academic research, lattes curriculum and research groups from national council for scientific and technological development database

• Autor(a) principal: Ramos-Carvalho, Priscila
• Data de Publicação: 2023
• Outros Autores: Gouveia, Fabio Castro, Ramos, Marcos Gonçalves
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Informação & Informação
• Texto Completo: https://ojs.uel.br/revistas/uel/index.php/informacao/article/view/47274
• topic: Inteligência Artificial; Plataforma Lattes; Grupos de Pesquisa; Biblioteca Digital de Teses e Dissertações

Objective: To map academic research in the scope of dissertations and theses carried out in postgraduate programs, as well as the scientific production regarding the geographical distribution, institutions, areas of knowledge, type of communication channel, coauthor network, and themes related to artificial intelligence. Methodology: The exploratory and descriptive research was based on quantitative methodological procedures through Bibliometrics and Content Analysis. The sources of information used were the Research Groups and the Lattes Platform of the National Council for Scientific and Technological Development, as well as the Brazilian Digital Library of Theses and Dissertations, of the Brazilian Institute of Information in Science and Technology. The tools chosen for data extraction, analysis, and visualization were scripLattes, Gephi, and IRaMuTeQ. Data collection was carried out in October 2022, with the Lattes defining the 30-year period. Results: 759 Research Groups, 20,400 Lattes curricula, and 3,073 thesis and dissertation records were identified. The most frequent areas of knowledge identified in the three bases covering the issue were the Exact and Earth Sciences, Engineering, and Applied Social Sciences. The most relevant regions in two of the bases were the Southeast and South. The institutions that stood out were the University of São Paulo and the Federal University of Santa Catarina, which bring together the largest scientific production on artificial intelligence in Brazil. Scientific publications are mostly concentrated in full articles published in journals and full papers in conferences. Some identified themes were related to the oil and gas, agriculture, education, and health sectors, as well as ethical and regulatory discussions. Conclusions: Researchers and research groups on artificial intelligence in Brazil seem to have experienced a period of growth. Although applications cross different areas of knowledge, the coauthor network of scientific production has shown to be little multidisciplinary.