A Second-Order Adaptive Network Model for Political Opinion Dynamics

This paper introduces a second-order adaptive network model for simulating political opinion dynamics, considering cognitive, affective, and social factors. The model, grounded in political psychology and communication theories, illustrates how individuals’ opinions evolve in response to external stimuli such as political parties and media. It also explores the impact of individuals’ reasoning abilities and initial viewpoints on their rationality and cognitive flexibility. Through simulation experiments, the paper demonstrates the model’s capacity to generate realistic outcomes such as homophily and polarization phenomena. It further discusses the model’s implications for mitigating misinformation spread and reducing polarization in political opinion dynamics, identifying key influencing factors and potential interventions. The paper contributes to computational politics by offering an innovative approach to modeling individual and collective opinion formation processes, acknowledging the complexity and adaptivity of cognitive, affective, and social dynamics.