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A Multi-Branch Feature Fusion Approach for Health Misinformation Detection and Propagation

arXiv · AI, language, vision and robotics · article · Aug 31, 2026 · UTC

This paper presents a multi-branch fusion framework for detecting and characterising the propagation of health misinformation in online social networks (OSNs). Grounded in the Elaboration Likelihood Model (ELM) and the Theory of Planned Behaviour (TPB), the model fuses transformer-based semantics with rhetorical cues, stance representations, and psychologically motivated proxies in a unified multi-task architecture. In addition to binary classification, we introduce the Cognitive Propagation Score (CPS), an interpretable post-hoc auxiliary score computed from psychologically motivated, text-de

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Evidence & attribution

First collected: 2026-09-21T06:21:59.299Z. This is not the publication date.