Misinformation Claim
Misinformation research focuses on detecting and mitigating the spread of false or misleading information, aiming to understand its creation, propagation, and impact. Current efforts utilize various machine learning models, including large language models (LLMs) and graph neural networks, often incorporating techniques like attention mechanisms and retrieval-augmented generation to improve accuracy and explainability. This field is crucial for addressing the societal harms of misinformation, informing the development of tools for fact-checking, social media moderation, and public health communication, and improving the reliability of AI systems themselves.
Papers
Health Misinformation in Social Networks: A Survey of IT Approaches
Vasiliki Papanikou, Panagiotis Papadakos, Theodora Karamanidou, Thanos G. Stavropoulos, Evaggelia Pitoura, Panayiotis Tsaparas
Monolingual and Multilingual Misinformation Detection for Low-Resource Languages: A Comprehensive Survey
Xinyu Wang, Wenbo Zhang, Sarah Rajtmajer