Why do Opinions and Actions Diverge? A Dynamic Framework to Explore the Impact of Subjective Norms
Chen Song, Vladimir Cvetkovic, Rong Su
TL;DR
The paper tackles the problem of why private opinions and public actions diverge by introducing a dynamic, agent-based framework that extends the classical HK bounded-confidence model with a utility-maximization layer for actions. It models opinions as private $x_i$ updated via neighbors’ observed actions and actions $y_i$ chosen to balance alignment with updated opinions and conformity to group norms through a commitment parameter $\phi$. Key contributions include (i) a generalized HK framework with continuous actions, (ii) separation of privately held opinions from publicly observable actions with sequential updates and subjective-norm considerations, and (iii) demonstration of diffusion phenomena—adoption, rejection, and enforcement of unpopular norms—and sensitivity to openness $\epsilon$ and commitment $\phi$. The findings show that higher openness and commitment promote opinion-action alignment, that network structure tends to impede global consensus, and that a small committed minority can trigger paradigm shifts or sustain unpopular norms, offering a potentially predictive lens for real-world social dynamics in cyber-physical-human systems.
Abstract
Socio-psychological studies have identified a common phenomenon where an individual's public actions do not necessarily coincide with their private opinions, yet most existing models fail to capture the dynamic interplay between these two aspects. To bridge this gap, we propose a novel agent-based modeling framework that integrates opinion dynamics with a decision-making mechanism. More precisely, our framework generalizes the classical Hegselmann-Krause model by combining it with a utility maximization problem. Preliminary results from our model demonstrate that the degree of opinion-action divergence within a population can be effectively controlled by adjusting two key parameters that reflect agents' personality traits, while the presence of social network amplifies the divergence. In addition, we study the social diffusion process by introducing a small number of committed agents into the model, and identify three key outcomes: adoption of innovation, rejection of innovation, and the enforcement of unpopular norms, consistent with findings in socio-psychological literature. The strong relevance of the results to real-world phenomena highlights our framework's potential for future applications in understanding and predicting complex social behaviors.