Misinformation Risk: Epidemiological and Social Models

Abstract

Understanding the mathematical dynamics of information propagation is critical for cognitive safety and crisis management. This study applies biological and sociolinguistic models to the diffusion of fake news in social media using the disinformation outbreak following the terrorist attack on Charlie Hebdo as case study. Biological models such as Susceptible-Infected-Recovered, Susceptible-Exposed-Infected-Recovered and sociolinguistic frameworks like Daley-Kendall and Maki-Thompson are fitted to real-world data using the nonlinear least squares method. The numerical results demonstrate that the Daley-Kendall model provides the most accurate fit to the observed data, outperforming the classical biological models. The findings indicate that the end of an explosive rumour is not governed by passive temporal recovery or incubation periods (as assumed in biological models) but by the mutual stifling. This suggests that in high-frequency social networks, information redundancy serves as the primary stabilizing mechanism. These insights propose that effective safety interventions should focus on accelerating network saturation to mitigate the spread of cognitive hazards.

Keywords: Risk Modelling, Cognitive Safety, Disinformation, Maki-thompson Model, Human Factors

DOI: 10.54941/ahfe1007919