UCLA

Political discourse is constantly in flux: the key issues, the actors that define the discourseare changing from moment to moment. Quantitative approaches to discourse are an impor- tant methodological tool that can help researchers measure the structure of and changes in discourse. However, existing approaches are often time-consuming and not scalable to large datasets. In this thesis, I apply a fully automated approach to discourse analysis that combines Structural Topic Modeling and Network Analysis. I apply the model to a novel dataset of the Brexit negotiations in British parliament. I find that the method captures the state of relations between actors and the progress in the negotiation process.