At the individual level, we analyze text generated in interactive environments such as online platforms, where interconnected actors influence one another in what they think, feel, and talk about.
In the wake of digitization, social-media platforms and publicly accessible repositories have become digital archives of public sentiment. Large corpora of text capture what people discuss at a scale and richness that neither qualitative nor survey research designs can match, and that are particularly well suited for studying social dynamics and collective phenomena as they unfold in interactive social contexts.
Our research is committed to applying and further developing computational text analysis as a rigorous tool for both thick description and causal inference in the social sciences. In our view, computational text analysis is not merely a technical innovation but a substantive expansion of what sociology can measure, model, and interpret, bridging quantitative scale with qualitative depth, and opening new avenues for studying phenomena that have long resisted systematic empirical inquiry.
