The project examines how and whether fascist ideology translates into violent actions in real life. The case study focuses on several fascist movements during the interwar period. The analysis is conducted in two parts: first, factual data about violent incidents is gathered and mapped; second, this data is cross-referenced with fascist publications to track changes in the frequency of violent rhetoric and calls for harm. Given the large volume of data, a computational approach is employed, using natural language processing and machine learning. Source material is extracted using OCR (Tesseract) and mapped for specific language patterns and sentiments.