DINÁMICA DE OPINIÓN EN REDES SOCIALES MULTICAPA

The opinion dynamics in multilayer networks were explored using a discrete evolution model. Three different network topologies (random, small-world, and scale-free) were combined to study three scenarios: two approximating real social systems and the other representing an idealized case. Various behaviors were observed in the evolution of the mean opinion state ⟨𝑆⟩ until it stabilized in the network. It was observed that stabilization occurred in most cases after more than 100 steps. Through the standard deviation for each configuration, the achievement of consensus was evidenced and it was found that some configurations require more than 600 steps to reach this state. Finally, the impact of intransigent individuals was analyzed, showing that the presence of at least one such individual in each layer results in a greater dispersion of opinions in the network.