Combining Voting and Abstract Argumentation to Understand Online Discussions

TL;DR

This paper introduces a novel, explainable approach combining voting theory and abstract argumentation to identify representative viewpoints in online discussions, enhancing interpretability of deliberative democracy platforms.

Contribution

It presents a new method integrating computational social choice and argumentation frameworks for better interpretation of online discussion outcomes.

Findings

Proposes voting rules for selecting representative discussion points.

Provides theoretical and simulation-based comparisons of methods.

Offers practical guidelines for method selection based on context.

Abstract

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.