Saved in:
Bibliographic Details
Main Authors: Korre, Katerina, Tsirmpas, Dimitris, Gkoumas, Nikos, Cabalé, Emma, Myrtzani, Danai, Evgeniou, Theodoros, Androutsopoulos, Ion, Pavlopoulos, John
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2503.01513
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866917188674256896
author Korre, Katerina
Tsirmpas, Dimitris
Gkoumas, Nikos
Cabalé, Emma
Myrtzani, Danai
Evgeniou, Theodoros
Androutsopoulos, Ion
Pavlopoulos, John
author_facet Korre, Katerina
Tsirmpas, Dimitris
Gkoumas, Nikos
Cabalé, Emma
Myrtzani, Danai
Evgeniou, Theodoros
Androutsopoulos, Ion
Pavlopoulos, John
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2503_01513
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Evaluation and Facilitation of Online Discussions in the LLM Era: A Survey
Korre, Katerina
Tsirmpas, Dimitris
Gkoumas, Nikos
Cabalé, Emma
Myrtzani, Danai
Evgeniou, Theodoros
Androutsopoulos, Ion
Pavlopoulos, John
Computation and Language
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.
title Evaluation and Facilitation of Online Discussions in the LLM Era: A Survey
topic Computation and Language
url https://arxiv.org/abs/2503.01513