Misinformation as a harm: structured approaches for fact-checking prioritization
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Abstract (arXiv)
In this work, we examine how fact-checkers prioritize which claims to fact-check and what tools may assist them in their efforts. Through a series of interviews with 23 professional fact-checkers from around the world, we validate that harm assessment is a central component of how fact-checkers triage their work. We also clarify the processes behind fact-checking prioritization, finding that they are typically ad hoc, and gather suggestions for tools that could help with these processes. To address the needs articulated by fact-checkers, we present a structured framework of questions to help fact-checkers negotiate the priority of claims through assessing potential harms. Our FABLE Framework of Misinformation Harms incorporates five dimensions of magnitude -- (social) Fragmentation, Actionability, Believability, Likelihood of spread, and Exploitativeness -- that can help determine the potential urgency of a specific message or claim when considering misinformation as harm. The result is a practical and conceptual tool to support fact-checkers and others as they make strategic decisions to prioritize their efforts. We conclude with a discussion of computational approaches to support structured prioritization, as well as applications beyond fact-checking to content moderation and curation.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 18 Dec 2023.
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Citing papers per year: 2024: 2; 2025: 1; 2026: 2.
5 papers.
- 2025Sword and Shield: Uses and Strategies of LLMs in Navigating Disinformationcited by 4
- 2024Diverse, but Divisive: LLMs Can Exaggerate Gender Differences in Opinion Related to Harms of Misinformationcited by 3
- 2024TrendFact: A Benchmark Towards Hotspot Perception in Automatic Fact-Checkingcited by 2
- 2026What do people want to fact-check?cited by 0
- 2026Beyond Binary Detection: A Multi-Dimensional Taxonomy of Cancer Misinformation on Redditcited by 0
- 2026Beyond Binary Detection: A Multi-Dimensional Taxonomy of Cancer Misinformation on Reddit14 Jul 2026
- 2026What do people want to fact-check?11 Feb 2026
- 2025Sword and Shield: Uses and Strategies of LLMs in Navigating Disinformation8 Jun 2025
- 2024TrendFact: A Benchmark Towards Hotspot Perception in Automatic Fact-Checking19 Oct 2024
- 2024Diverse, but Divisive: LLMs Can Exaggerate Gender Differences in Opinion Related to Harms of Misinformation29 Jan 2024