{
  "id": 12978,
  "url": "https://arxiv.org/abs/2607.20031v1",
  "title": "Visual Indicators to Increase the Detection of Linguistic Media Bias",
  "summary": "The influence of linguistic bias in online news articles is a growing concern, particularly in the context of shaping public opinion and rising political polarization. While there is a growing body of literature on indicators for misinformation, none have been sufficiently tested to counteract the influence of media bias. Hence, we design six indicators (Bias Bar, Bias Gauge, Bias Highlights, Political Scale, Sentiment Scale, and Trust Score) and test their impact on linguistic bias detection an",
  "authors": "Smi Hinterreiter, Anna Chelsea Bahß, Ann-Christin Gah, Timo Spinde, Isao Echizen, Marc Erich Latoschik",
  "category": "research",
  "topics": "bias-fairness,misinformation",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-22T11:18:55.000Z",
  "fetched_at": "2026-07-23T05:10:49.458Z",
  "source_slug": "x-arxiv-cs-hc",
  "source_name": "arXiv cs.HC",
  "source_homepage": "https://arxiv.org/list/cs.HC/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/12978",
  "original_url": "https://arxiv.org/abs/2607.20031v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}