Toward Systemic Immunization: Modeling Disinformation Propagation Dynamics With Intervention and Network-Driven Risk...

The systemic diffusion of disinformation on social media poses escalating threats to digital societies, causing cognitive distortion, financial instability, and public crises that demand precision governance. Existing models exhibit critical limitations. For example, epidemiological approaches neglect individual decision heterogeneity, game-theoretic frameworks assume complete rationality, and cognitive psychology paradigms lack cross-scale risk coupling mechanisms. We propose a novel disinformation propagation model which incorporates (a) individual-level dynamics via risk perception thresholds, decision sensitivity, and cognitive inertia; (b) network-level equations that formalize topology-driven risk cascades; and (c) intervention analytics that quantify minimum effective intensity thresholds. Specifically, we do the following main work: (1) We construct a network propagation model without authoritative intervention and prove equilibrium existence while it is not unique; (2) we develop a dual-index system of nodal risk exposure and vulnerability to identify critical superspreaders; (3) we formulate an intervention model combining cognitive correction with propagation suppression, prove equilibrium existence under interventions, and derive sufficient conditions for unique convergence; (4) we establish the bounded intervention efficacy theorem, ensuring predictable outcomes when intervention intensity exceeds critical thresholds; (5) we derive lower bounds on convergence time and compare convergence rates between intervention and nonintervention scenarios; and (6) we quantify how individual heterogeneity and intervention intensity jointly modulate systemic risks. These findings provide a comprehensive theoretical framework for constructing a disinformation immune system. By clarifying the coupling dynamics between propagation mechanisms and intervention strategies, our research offers quantifiable decision-making tools for digital governance.