{
  "id": 17772,
  "url": "https://arxiv.org/abs/2607.02900",
  "title": "Angry but Accurate: Detecting and Profiling the Counter-Misinformation Ecosystem on Twitter",
  "summary": "arXiv:2607.02900v2 Announce Type: replace-cross Abstract: On social media, many users actively push back against false claims. Understanding who pushes back and how they do so matters, as this corrective activity is central to how misinformation is contested. We study this counter-misinformation ecosystem at scale: applying a domain-specific NLI model from our prior work to a large corpus of COVID-19 tweets, we classify 264,737 posts as supporting or opposing false claims and compare 23 user- an",
  "authors": "Eun Cheol Choi, Emilio Ferrara",
  "category": "research",
  "topics": "misinformation",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-10T04:00:00.000Z",
  "fetched_at": "2026-08-10T05:10:00.488Z",
  "source_slug": "arxiv-cscy",
  "source_name": "arXiv cs.CY",
  "source_homepage": "https://arxiv.org/list/cs.CY/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/17772",
  "original_url": "https://arxiv.org/abs/2607.02900",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}