Political discourse is constantly in flux: the key issues, the actors that define the discourse are changing from moment to moment. Quantitative approaches to discourse are an important 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.