title: Classifying Speech Acts in Political Communication: A Transformer-based Approach with Weak Supervision and Active Learning
abstract: We present a study on the automatic classification of speech acts in the domain of political communication, based on J. R. Searle's classification of illocutionary acts.Our research involves creating a dataset using the US State of the Union corpus and the UN General Debate corpus (UNGD) as data sources.To overcome limited labelled data, we employ a combination of weak supervision and active learning techniques for dataset creation and model training.Through various experiments, we investigate t
journal: Annals of Computer Science and Information Systems