Abstract
Technological Forecasting and Social Change (TFSC) is one of the most prominent journals to focus on the methodologies and practices of technological forecasting and futures studies. This study aims to analyse the topical structure of TFSC and track the most cited articles published in the journal using a combination of a structural topic model (STM) and bibliometric analysis. The STM reveals 18 prominent topics in TFSC, and the topical quality of the STM results is verified based on semantic coherence and topic exclusivity scores as well as an assessment of the correlations among topics. The STM also tracks the temporal variations in topical prevalence that occurred from 1969 to 2022, shedding light on the changing popularity of each topic. The bibliometric analysis presents a decade-by-decade perspective on the most cited articles and the geographical dispersion of authors affiliated with TFSC, thereby providing a truly global perspective on the journal's publishing activity.