Fuzzy c-Means Clustering Based Polarization Assessment in Intelligent Argumentation System for Collaborative Decision Support

Abstract

Intelligent argumentation system facilitates stakeholders to exchange dialogue over issues and provides decision support by capturing rationale of the stakeholders through arguments. In argumentation process, stakeholders tend to polarize on their opinions and form polarization groups. A method [1] was developed earlier to identify polarization groups, however, polarization groups tend to overlap to a certain degree and each stakeholder may be a member of multiple polarization groups to varied degrees. Quantifying stakeholders' membership in multiple polarization groups in argumentation for collaborative decision making is not addressed earlier. We present an approach using fuzzy clustering algorithm to address this issue and evaluate the approach using an argumentation tree built by twenty four stakeholders.