Why We Experience Society Differently: Intrinsic Dispositions as Drivers of Ideological Complexity in Adaptive Social Networks

Abstract

Understanding the emergence of inequality in complex systems requires attention to both structural dynamics and intrinsic heterogeneity. In the context of opinion dynamics, traditional models relied on static snapshots or assumed homogeneous agent behavior, overlooking how diverse cognitive dispositions shape belief evolution. While some recent models introduce behavioral heterogeneity, they typically focus on macro-level patterns, neglecting the unequal and individualized dynamics that unfold at the agent level. In this study, we analyze an adaptive social network model where each agent exhibits one of three behavioral tendencies-homophily, neophily (attention to novelty), or social conformity-and measure the complexity of individual opinion trajectories using normalized Lempel-Ziv complexity. We find that the dynamics are often counterintuitive-homophilic agents, despite seeking similarity, become increasingly unpredictable; neophilic agents, despite pursuing novelty, exhibit constrained exploration; and conformic agents display a two-phase trajectory, transitioning from early stability to later unpredictability. Moreover, these patterns remain similar across diverse network settings, suggesting that internal behavioral dispositions - rather than external environment alone - play a central role in shaping long-term opinion unpredictability. The broader implication is that individuals' experiences of ideological volatility, uncertainty, or stability are not merely environmental, but may be endogenously self-structured through their own cognitive tendencies. These results establish a novel individual-level lens on opinion dynamics, where the behavioral identity of agents serves as a dynamical fingerprint in the evolution of belief systems, and gives rise to persistent disparities in dynamical experience within self-organizing social systems, even in structurally similar environments.