Modelo de opiniões extremas em redes complexas

Abstract

In this work, we investigate the dynamics of opinion in complex networks, focusing on the variation of the stubbornness parameter (a). We reproduce and analyze the opinion model that proposes activation rules with this parameter (RAMOS et al., 2015), examining phase transitions from cluster formation. Our results highlight the system’s sensitivity to initial conditions and reveal that the parameter a plays a significant role in phase transitions. We observe that for smaller values of a, transitions are more abrupt, indicating greater flexibility in individual opinions. As a increases, resistance to change intensifies, resulting in smoother transitions. The construction of the phase diagram for values of ⟨k⟩ = 5 and ⟨k⟩ = 4 validates the original model’s proposition of a critical transition from moderate to extreme views, characterized by nonlinear behavior.