Community Moderation and the New Epistemology of Fact Checking on Social Media
원문 초록
Social media platforms have traditionally relied on internal moderation teams and partnerships with independent fact-checking organizations to identify and flag misleading content. Recently, however, platforms including X (formerly Twitter) and Meta have shifted towards community-driven content moderation by launching their own versions of crowd-sourced fact-checking -- Community Notes. If effectively scaled and governed, such crowd-checking initiatives have the potential to combat misinformation with increased scale and speed as successfully as community-driven efforts once did with spam. Nevertheless, general content moderation, especially for misinformation, is inherently more complex. Public perceptions of truth are often shaped by personal biases, political leanings, and cultural contexts, complicating consensus on what constitutes misleading content. This suggests that community efforts, while valuable, cannot replace the indispensable role of professional fact-checkers. Here we systemically examine the current approaches to misinformation detection across major platforms, explore the emerging role of community-driven moderation, and critically evaluate both the promises and challenges of crowd-checking at scale.
함께 살펴볼 논문
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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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