Advancing Deliberative Discourse Measurement: The Intersection with Computational Abstract Argumentation in Discourse Quality Evaluations

This research investigates the potential of computational argumentation, specifically the application of the Abstract Argumentation Framework (AAF), to enhance the evaluation of deliberative quality in public discourse. It focuses on integrating AAF and its related semantics with the Discourse Quality Index (DQI), which is a reputable indicator of deliberative quality. The motivation is to overcome the DQI’s constraints using the AAF’s formal and logical features by addressing dependency on hand coding and attention to specific speech acts. This is done by exploring how the AAF can identify conflicts among arguments and assess the acceptability of different viewpoints, potentially leading to a more automated and objective evaluation of deliberative quality. A pilot study is conducted on the topic of abortion to illustrate the proposed methodology. The findings of this research demonstrate that AAF methods can improve discourse analysis by automatically identifying strong arguments through conflict resolution strategies. They also emphasise the potential of the proposed procedure to mitigate the dependence on manual coding and improve deliberation processes.