This article explores advancements in artificial intelligence (AI) within scholarly research and practical applications in the journalistic subgenre of fact-checking in Europe and Latin America using a mixed-method approach.
Building on a prior systematic review of 348 peer-reviewed publications on algorithm-driven journalism, this study examined articles on fact-checking to outline the field. The review identified European and Latin American countries as both prominent and underrepresented, guiding subsequent investigation stages.
A quantitative content analysis of 3,154 verification articles across eight countries (AR, BR, CL, VZ, the UK, DE, PT, SP) and 23 organisations in both continents was conducted to observe the most used automated verification tools.
A qualitative analysis of the organisations’ websites and promotional materials, which tracks in-house AI projects aimed at monitoring, detecting, verifying, and disseminating claims, was conducted.
The analysis revealed a significant imbalance in scholarly production and a dearth of studies combining algorithm-driven journalism with fact-checking. Fact-checking organisations predominantly employ basic automated tools like reverse image search and geolocation apps, indicating a trend towards convergence.
However, proprietary automated tools for misinformation detection, monitoring, and compilation show regional disparities, with many being based in Europe and funded by major entities such as Google, EU projects, and the IFCN.
