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Pareto-Improvement-Driven Opinion Dynamics Explaining the Emergence of Pluralistic Ignorance

Yuheng Luo,Chuanzhe Zhang,Qingsong Liu,Hai Zhu,Wenjun Mei

Published 2025 in IEEE Conference on Decision and Control

ABSTRACT

Opinion dynamics studies how interpersonal influence and social network structures shape the evolution of public opinions. Recently, various models of opinion dynamics have been proposed within a game-theoretic framework, where interpersonal influence mechanisms are captured by players’ cost functions, reflecting their motivations. Conventionally, when players have multiple motivations, an aggregated cost function is constructed by summing individual cost functions corresponding to different motivations. However, whether these "costs" in people’s minds are interchangeable remains a subject of debate. In this paper, we propose an opinion dynamics model based on a multi-objective game framework. In our model, individuals experience two distinct costs: social pressure from disagreeing with others and cognitive dissonance from deviating from the truth. Opinion updates are modeled as Pareto improvements between these two cost functions. This approach provides a parsimonious explanation for the emergence of pluralistic ignorance—where individuals may "agree" on something untrue, even though they all know the underlying truth. We conduct a theoretical analysis of the proposed model, establishing conditions for the almost-sure convergence and for the prevalence of truth.

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