Occupational health and safety and data mining: a bibliometric analysis - Rafael, Camila; Peternella, Mateus Vicente; Lavezo dos Reis, Beatriz; Leal, Gislaine Camila Lapasini; Thom de Souza, Rodrigo Clemente; Galdamez, Edwin Vladimir Cardoza (Revista Gestão da Produção Operações e Sistemas, 2021)
Purpose - This article aims to carry out a bibliometric analysis on data mining and occupational health and safety, covering the period between 2008 and 2020, for seven scientific databases and 68 articles. Theoretical framework - This study was theoretically based on concepts that involve data mining, machine learning and occupational health and safety. Design/methodology/approach - The selected articles were submitted to a statistical analysis, together with the evaluation of one of the bibliometric laws (Bradford’s Law), comprising a number of citations, journals, authors, countries of origin, publication categories and an evaluation of production over the years. Findings - As a result, it was found that the most influential journal was Safety Science, and Taiwan was the leading country in terms of articles produced, with an average of 115 citations per article. The best-ranked journals related to Engineering and Health, both corresponding to 30% of the selected articles and journals. Originality/value - This study provides some insights into the growth of the data mining area together with occupational health and safety. Keywords - Bibliometrics analysis. Occupational health and safety. Data mining.