Stochastic Delayed Dynamics of Rumor Propagation with Awareness and Fact-Checking

TL;DR

This paper develops a stochastic delayed differential model for rumor spread during infodemics, incorporating human response delays, skepticism, and fact-checking, with stability analysis and simulation validation.

Contribution

It introduces a novel stochastic delayed differential model that captures delays and randomness in rumor propagation, providing stability analysis and insights into intervention effectiveness.

Findings

Timely awareness and fact-checking reduce misinformation spread.

The model's stability depends on reproduction number conditions.

Simulations show delays increase outbreak severity.

Abstract

This paper presents a stochastic delayed differential model for rumor propagation during infodemic that incorporates human behavioral response, public skepticism and fact-checking mechanisms. A discrete time delay is introduced to model natural lags in information processing and institutional response. Additionally, we adopt additive stochastic perturbations to model random fluctuations in social interaction and exposure. We present a rigorous stability analysis of the proposed rumor transmission model and derive convergence guarantees under reproduction number conditions. We also validate the model by numerical simulations and analyze the outbreak severity and quantify uncertainty under variable information processing delays. The results highlight the importance of timely awareness and fact-checking interventions for mitigating misinformation spread during pandemics