详细信息
- 来源站点
- ArXiv CS.CL
- 作者
- Alejandro Buitrago L\'opez, Alberto Ortega Pastor, Javier Pastor-Galindo, Jos\'e A. Ruip\'erez-Valiente
- 文章类型
- NEWS
- 语言
- en
- 发布日期
- 2026-05-28
摘要
arXiv:2605.28598v1 Announce Type: new Abstract: LLM-powered social agents are increasingly used to simulate online social behavior, yet their realism remains difficult to validate. Existing work has largely relied on general-purpose benchmarks, while less attention has been paid to short, reactive discourse such as audience replies to online news. In this paper, we evaluate whether LLM-generated reactions to Spanish online news reproduce measurable properties of real audience discourse. Using the Hatemedia dataset, we pair 5,631 news items with 58,555 real audience reactions, and generate a matched synthetic dataset using five LLMs under a shared experimental setting. We compare real and synthetic reactions across three dimensions: hate speech, sentiment, and semantic alignment, considering both off-the-shelf and fine-tuned generation.