Disentangling Fact from Sentiment: A Dynamic Conflict-Consensus Framework for Multimodal Fake News Detection
Published:Dec 19, 2025 10:20
•1 min read
•ArXiv
Analysis
This article introduces a research paper on fake news detection. The focus is on a multimodal approach, suggesting the use of different data types (e.g., text, images). The framework aims to distinguish between factual information and subjective sentiment, likely to improve accuracy in identifying fake news. The 'Dynamic Conflict-Consensus' aspect suggests an iterative process where different components of the system might initially disagree (conflict) but eventually converge on a consensus.
Key Takeaways
- •Focus on multimodal fake news detection.
- •Employs a 'Dynamic Conflict-Consensus' framework.
- •Aims to differentiate fact from sentiment.
Reference
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