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This research aimed to create a more effective way to detect fake pandemic news on social media.

Dynamic Multi-Scale Hypergraph Neural Network for Fake Pandemic News Detection in Social Media

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This research aimed to create a more effective way to detect fake pandemic news on social media.
Developed a dynamic multi-scale hypergraph neural network framework
Employed a cross-time fusion mechanism for integrating temporal dynamics
Extracted local user behavior features using propagation tree forests
The framework significantly outperformed existing methods
Achieved higher accuracy and F1 scores in detection tasks
Promising results, although generalizability may be impacted by dataset limitations

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A framework demonstrates improved fake news detection in social media, suggesting enhanced public health safety.

Gao et al. (2026) studied this question.

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