DCCF disentangles fact and sentiment in multimodal data, applies dynamic polarization to extract conflicts, and uses a conflict-consensus mechanism to improve fake news detection accuracy by 3.52% on average over baselines.
Ken: Knowledge augmentation and emotion guidance network for multimodal fake news detection,
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Disentangling Fact from Sentiment: A Dynamic Conflict-Consensus Framework for Multimodal Fake News Detection
DCCF disentangles fact and sentiment in multimodal data, applies dynamic polarization to extract conflicts, and uses a conflict-consensus mechanism to improve fake news detection accuracy by 3.52% on average over baselines.