Dalveren, Gonca Gökçe MenekşeGurcan, FatihAyaz, AhmetDalveren, Gonca Gokce MenekseDerawi, MohammadInformation Systems Engineering2024-07-052024-07-05202332071-105010.3390/su151398542-s2.0-85164913188https://doi.org/10.3390/su15139854https://hdl.handle.net/20.500.14411/2220GURCAN, Fatih/0000-0001-9915-6686; Menekse Dalveren, Gonca Gokce/0000-0002-8649-1909; Ayaz, Ahmet/0000-0003-1405-0546The widespread use of business intelligence products, services, and applications piques the interest of researchers in this field. The interest of researchers in business intelligence increases the number of studies significantly. Identifying domain-specific research patterns and trends is thus a significant research problem. This study employs a topic modeling approach to analyze domain-specific articles in order to identify research patterns and trends in the business intelligence field over the last 20 years. As a result, 36 topics were discovered that reflect the field's research landscape and trends. Topics such as "Organizational Capability", "AI Applications", "Data Mining", "Big Data Analytics", and "Visualization" have recently gained popularity. A systematic taxonomic map was also created, revealing the research background and BI perspectives based on the topics. This study may be useful to researchers and practitioners interested in learning about the most recent developments in the field. Topics generated by topic modeling can also be used to identify gaps in current research or potential future research directions.eninfo:eu-repo/semantics/openAccessbusiness intelligencetopic modelingtext miningtrend analysismachine learningArticleQ2Q21513WOS:001028127500001