Dissecting meaning structures of the social world has always been the domain of interpretive methodologies such as ethnography, grounded theory, or hermeneutics. However, researchers within social sciences and humanities are now increasingly relying on computational methods to study complex social and cultural phenomena. The uptake of agent-based computational modelling, large language models, social and visual network analyses, text mining or predictive modelling with machine learning — and the relatively open-ended nature of the data they produce — allows researchers to answer new questions that are relevant for understanding emergent social practices and the changing conditions for knowledge production and meaning-making. 
 

This two-day workshop is organized around discussions that address key methodological issues in the intersection of interpretive and computational research approaches. The aim is to provide the building blocks for exploring their methodological complementarity, and for reflecting on how such a cross-fertilization can contribute to the research programmes of social and humanities disciplines.