在大语言模型时代评估和促进在线讨论：一篇综述
Evaluation and Facilitation of Online Discussions in the LLM Era: A Survey
AI总结：
本文综述了大语言模型时代在线讨论评估与促进方法，提出新的评估分类、干预策略及未来研究方向。
摘要：
我们呈现了一篇关于评估和提高在线讨论质量的方法综述，重点在于大语言模型（LLM）的潜力。尽管在线讨论理论上旨在促进相互理解，但它们往往退化为有害的交流，如仇恨言论，威胁社会凝聚力和民主价值观。近期大语言模型的进步使人工智能调解代理不仅能监管内容，还能主动提高互动质量。我们的综述结合了自然语言处理和社会科学的想法，提供了（a）讨论质量评估的新分类法，（b）干预和促进策略的概述，（c）以及新的对话促进数据集分类法，（d）从技术和社会角度的良好的实践和未来研究方向路线图。
英文摘要：
We present a survey of methods for assessing and enhancing the quality of online discussions, focusing on the potential of LLMs. While online discourses aim, at least in theory, to foster mutual understanding, they often devolve into harmful exchanges, such as hate speech, threatening social cohesion and democratic values. Recent advancements in LLMs enable artificial facilitation agents to not only moderate content, but also actively improve the quality of interactions. Our survey synthesizes ideas from NLP and Social Sciences to provide (a) a new taxonomy on discussion quality evaluation, (b) an overview of intervention and facilitation strategies, (c) along with a new taxonomy of conversation facilitation datasets, (d) an LLM-oriented roadmap of good practices and future research directions, from technological and societal perspectives.
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。
