Researchers have developed a novel multi-branch fusion framework designed to detect and analyze the spread of health misinformation on social media. This model integrates transformer-based semantic analysis with rhetorical cues and psychological factors, drawing on established theories like the Elaboration Likelihood Model and the Theory of Planned Behaviour. Beyond simple classification, the framework introduces a Cognitive Propagation Score (CPS) to estimate diffusion risk using interpretable, text-derived metrics such as argument complexity and emotional intensity. Experiments on benchmark datasets demonstrate high performance in both detection and propagation ranking, outperforming existing literature baselines. AI
IMPACT This framework could enhance the transparency and scalability of monitoring health misinformation online by combining AI with psychological theories.
RANK_REASON This is a research paper detailing a new model and framework for misinformation detection. [lever_c_demoted from research: ic=1 ai=1.0]
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