Machine Learning for Enhancing Deliberation in Online Political Discussions and Participatory Processes: A Survey

TL;DR

This survey reviews how machine learning can improve online political discussions by addressing issues, enhancing deliberation quality, and supporting platform design, based on existing tools, challenges, and future directions.

Contribution

It provides a comprehensive overview of AI tasks, tools, and challenges in enhancing deliberation in online political participation through machine learning.

Findings

Identification of key AI tasks for improving deliberation

Overview of existing AI-supported platforms

Assessment of current AI effectiveness and challenges

Abstract

Political online participation in the form of discussing political issues and exchanging opinions among citizens is gaining importance with more and more formats being held digitally. To come to a decision, a thorough discussion and consideration of opinions and a civil exchange of arguments, which is defined as the act of deliberation, is desirable. The quality of discussions and participation processes in terms of their deliberativeness highly depends on the design of platforms and processes. To facilitate online communication for both participants and initiators, machine learning methods offer a lot of potential. In this work we want to showcase which issues occur in political online discussions and how machine learning can be used to counteract these issues and enhance deliberation. We conduct a literature review to (i) identify tasks that could potentially be solved by artificial intelligence (AI) algorithms to enhance individual aspects of deliberation in political online discussions, (ii) provide an overview on existing tools and platforms that are equipped with AI support and (iii) assess how well AI support currently works and where challenges remain.