Abstract
This thesis examines the use of neural network methods for classifying parliamentary speeches by textual content. It introduces previous work in the field using traditional methods, and discusses aspects of the Talk of Norway (ToN) corpus, while covering the theoretical background behind neural methods in detail. Detailed analyses are given for various architectures applied to the task.