利用机器学习增强在线政治讨论和参与过程中的 deliberation：一篇综述
Machine Learning for Enhancing Deliberation in Online Political Discussions and Participatory Processes: A Survey
AI总结：
本文探讨了如何利用机器学习技术提升在线政治讨论的 deliberation 质量，通过文献综述识别AI可解决的讨论优化任务，并评估现有AI支持工具的成效与挑战。
摘要：
以公民讨论政治问题和交换意见的形式的在线政治参与正变得越来越重要，随着更多数字格式的出现。为了做出决定，需要深入讨论和考虑意见，并进行文明的论点交流，这被定义为deliberation的行为。讨论和参与过程的deliberativeness质量高度依赖于平台和过程的设计。为了促进参与者和发起者的在线沟通，机器学习方法提供了大量潜力。本文旨在展示在线政治讨论中出现的问题以及机器学习如何用于对抗这些问题并增强deliberation。我们进行了文献综述，以（i）识别可能由人工智能（AI）算法解决的讨论优化任务，（ii）提供现有配备AI支持的工具和平台的概述，以及（iii）评估AI支持目前的效果以及仍存在的挑战。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
