The Intended Uses of Automated Fact-Checking Artefacts: Why, How and Who
원문 초록
Automated fact-checking is often presented as an epistemic tool that fact-checkers, social media consumers, and other stakeholders can use to fight misinformation. Nevertheless, few papers thoroughly discuss how. We document this by analysing 100 highly-cited papers, and annotating epistemic elements related to intended use, i.e., means, ends, and stakeholders. We find that narratives leaving out some of these aspects are common, that many papers propose inconsistent means and ends, and that the feasibility of suggested strategies rarely has empirical backing. We argue that this vagueness actively hinders the technology from reaching its goals, as it encourages overclaiming, limits criticism, and prevents stakeholder feedback. Accordingly, we provide several recommendations for thinking and writing about the use of fact-checking artefacts.
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RealFactBench: A Benchmark for Evaluating Large Language Models in Real-World Fact-Checking
SUCEA: Reasoning-Intensive Retrieval for Adversarial Fact-checking through Claim Decomposition and Editing
Entity-aware Cross-lingual Claim Detection for Automated Fact-checking
When Claims Evolve: Evaluating and Enhancing the Robustness of Embedding Models Against Misinformation Edits
SemViQA: A Semantic Question Answering System for Vietnamese Information Fact-Checking
Beyond Translation: LLM-Based Data Generation for Multilingual Fact-Checking
토론
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