Modeling social conformity and peer pressure in opinion dynamics: the role of dynamic interaction structures

With the advent of modern media platforms, the dissemination of information has become faster and more far-reaching than ever before. These platforms amplify susceptibility to societal influences, as individuals respond to widely circulating information while being shaped by the perspectives of those around them. By aligning with others’ opinions, individuals contribute to establishing shared norms through both macroscopic and microscopic influences. This paper explores the roles of these influences—social conformity at the population-wide level and peer pressure at the localized level—in shaping opinion dynamics within today’s information-rich environment. Building on the Hegselmann-Krause opinion dynamics model, we introduce modifications to incorporate peer pressure through three modes of dynamic social circles. While conformity and peer pressure have been studied previously, we focus specifically on how properties and behaviors evolve in an opinion-dependent manner from both individual and social circle perspectives. Furthermore, we incorporate radical agents, characterized by resistance to influence. However, unlike radicals as referred to the stubborn agents commonly discussed in previous literature, our radical agents adjust their behavior based on their position in the opinion spectrum rather than remaining entirely fixed in their views. Simulations reveal that removing agents with distant opinions from social circles facilitates population convergence more than adding agents with similar opinions. Our model suggests that increasing the number of agents within social circles accelerates opinion shifts. Similarly, broadening confidence bounds fosters cluster formation. In addition, a higher initial number of radical agents makes it more likely for non-radical agents to adopt radical views. Likewise, when agents are influenced more by macroscopic rather than microscopic forces, radicalization becomes more likely. Together, one or more of these dynamics drive convergence between radical and non-radical agents.