Evaluation and Facilitation of Online Discussions in the LLM Era: A Survey
This survey addresses the challenge of improving online discourse quality for social cohesion and democratic values, but it is incremental as it synthesizes existing ideas without introducing new methods.
The paper tackles the problem of online discussions often devolving into harmful exchanges by surveying methods to assess and enhance their quality using LLMs, resulting in new taxonomies for evaluation and datasets, and a roadmap for future research.
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.