English

Commenotes: Synthesizing Organic Comments to Support Community-Based Fact-Checking

Human-Computer Interaction 2025-09-16 v1

Abstract

Community-based fact-checking is promising to reduce the spread of misleading posts at scale. However, its effectiveness can be undermined by the delays in fact-check delivery. Notably, user-initiated organic comments often contain debunking information and have the potential to help mitigate this limitation. Here, we investigate the feasibility of synthesizing comments to generate timely high-quality fact-checks. To this end, we analyze over 2.2 million replies on X and introduce Commenotes, a two-phase framework that filters and synthesizes comments to facilitate fact-check delivery. Our framework reveals that fact-checking comments appear early and sufficiently: 99.3\% of misleading posts receive debunking comments within the initial two hours since post publication, with synthesized \textit{commenotes} successfully earning user trust for 85.8\% of those posts. Additionally, a user study (N=144) found that the synthesized commenotes were often preferred, with the best-performing model achieving a 70.1\% win rate over human notes and being rated as significantly more helpful.

Keywords

Cite

@article{arxiv.2509.11052,
  title  = {Commenotes: Synthesizing Organic Comments to Support Community-Based Fact-Checking},
  author = {Shuning Zhang and Linzhi Wang and Dai Shi and Yuwei Chuai and Jingruo Chen and Yunyi Chen and Yifan Wang and Yating Wang and Xin Yi and Hewu Li},
  journal= {arXiv preprint arXiv:2509.11052},
  year   = {2025}
}
R2 v1 2026-07-01T05:35:04.946Z