Ginger Cannot Cure Cancer: Battling Fake Health News with a Comprehensive Data Repository
원문 초록
Nowadays, Internet is a primary source of attaining health information. Massive fake health news which is spreading over the Internet, has become a severe threat to public health. Numerous studies and research works have been done in fake news detection domain, however, few of them are designed to cope with the challenges in health news. For instance, the development of explainable is required for fake health news detection. To mitigate these problems, we construct a comprehensive repository, FakeHealth, which includes news contents with rich features, news reviews with detailed explanations, social engagements and a user-user social network. Moreover, exploratory analyses are conducted to understand the characteristics of the datasets, analyze useful patterns and validate the quality of the datasets for health fake news detection. We also discuss the novel and potential future research directions for the health fake news detection.
함께 살펴볼 논문
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DCR: Quantifying Data Contamination in LLMs Evaluation
Synergizing LLMs with Global Label Propagation for Multimodal Fake News Detection
KGAlign: Joint Semantic-Structural Knowledge Encoding for Multimodal Fake News Detection
Multimodal Fake News Detection: MFND Dataset and Shallow-Deep Multitask Learning
A Python Tool for Reconstructing Full News Text from GDELT
Multi-view autoencoders for Fake News Detection
토론
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