Dynamic Model of Echo Chamber Formation in Social Networks: Integration of Stochastic Differential Equations and Evolutionary Graphs

<p dir="ltr">This study investigates the mechanisms of echo chamber formation in social networks, taking into account the evolutionary dynamics of user connections. A combined model is proposed that integrates stochastic differential equations (SDEs) describing the evolution of users’ opinions with dynamic link adaptation based on the mechanisms of evolutionary graphs. A mechanism of dynamic link updating based on opinion similarity is introduced, allowing the model to capture both the processes of radicalization and potential pathways to consensus. Numerical simulations are performed to analyze how model parameters influence the stability of the system and the dynamics of the informational environment. The results confirm that algorithmic recommendation mechanisms significantly enhance polarization, while random external perturbations can alter the network’s developmental trajectory. The proposed approach provides a deeper understanding of the formation of informational clusters and offers tools for developing effective strategies to reduce the negative impact of echo chambers.</p>