Modelling Argumentative Behaviour in Parliamentary Debates: Data Collection, Analysis and Test Case

In this paper we apply the information state update (ISU) machinery to tracking and understanding the argumentative behaviour of participants in a parliamentary debate in order to predict its outcome. We propose to use the ISU approach to model the arguments of the debaters and the support/attack links between them as part of the formal representations of a participant’s information state. We first consider the identification of claims and evidence relations to their premises as an argument mining task. It is not sufficient, however, to indicate what relations occur without establishing how these relations are created and verified during the interaction. For this purpose the model requires a detailed specification of the creation, maintenance and use of shared beliefs. The ISU model provides procedures for incorporating beliefs and expectations shared between speaker and hearers in the tracking model. To evaluate the content of the tracked information states, we compare them to those of the human ‘concluder’ who wraps up a debate, stating the claims which the majority of the debaters have agreed on.