Machine Learning in Islamic Economics and Finance: A Comparative Bibliometric Analysis with The Conventional Field - Kazak, Hasan; Arik, Boran; Akcan, Ahmet Tayfur (International Journal of Economics, Management and Accounting, 2025)
The aim of the study is to perform a bibliometric mapping analysis of machine learning research on Islamic economics and finance in the Web of Science (WOS) database. In the study, a bibliometric analysis was performed on all studies written on the topic of “Machine Learning” with WOS data and in the fields of “Economics” and “Finance” as well as “Islamic Economics” and “Islamic Finance.” The tool VOSviewer (1.6.18) was used to classify the data within the research framework. As a result of the analysis, authoritative authors, journals, institutions, and the most frequently referenced sources in the field were identified. Besides that, information about the country that has done the most work in the field was also expressed as a result of the VOSViewer (1.6.18) program. When evaluating the literature, no study was identified that includes both economic and financial concerns on machine learning and presents a comparative bibliometric mapping analysis by studying Islamic economics and Islamic finance issues. It is believed that this study will contribute to literature in this regard.