Abstract
This paper presents a text-based method for measuring illiberalism. Our approach distinguishes between political actors within the same country and is sensitive to different subtypes of illiberalism—such as anti-pluralism, nationalism, religious fundamentalism, and the villainization of political opponents. The model combines word embeddings, trained on actor- and time-specific text, with dictionaries of liberal and illiberal terms. We apply our measures to 67 political parties across seven European legislatures (1996-2022) and two issues: gender politics and immigration. Our results identify differences in the degrees and varieties of illiberalism across countries, systematically demonstrating illiberalism’s political relevance.