2024/02/08 by Michael Bernreiter, Jan Maly, Bernreiter, Michael +5
Computer Science · Psychology · Social Sciences · #Computer Science and Game Theory (cs.GT) #FOS: Computer and information sciences #Innovative Teaching and Learning Methods #Intelligent Tutoring Systems and Adaptive Learning #Online and Blended Learning
paper · pdf · doi:10.48550/arxiv.2402.05895
openalex publication_date 2024/02/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/03
Online discussion platforms are a vital part of the public discourse in a deliberative democracy. However, how to interpret the outcomes of the discussions on these platforms is often unclear. In this paper, we propose a novel and explainable method for selecting a set of most representative, consistent points of view by combining methods from computational social choice and abstract argumentation. Specifically, we model online discussions as abstract argumentation frameworks combined with information regarding which arguments voters approve of. Based on ideas from approval-based multiwinner voting, we introduce several voting rules for selecting a set of preferred extensions that represents voters' points of view. We compare the proposed methods across several dimensions, theoretically and in numerical simulations, and give clear suggestions on which methods to use depending on the specific situation.