An Investigation into the Causal Mechanism of Political Opinion Dynamics: A Model of Hierarchical Coarse-Graining with Community-Bounded Social Influence

TL;DR

The paper addresses how political opinions evolve from micro beliefs to macro consensus and how polarization arises in democratic societies. It develops an agent-based CODA framework with hierarchical coarse-graining and labels to study upward and downward causation, incorporating inter-community migration as a source of higher-level connectivity. The results reveal three information-integration regimes—Independent, Parallel, and Iterative—whose existence and properties depend on label-switching probability and inputs, with the Iterative regime featuring three phases and transient diversity that yields a more informed, slower path to consensus. The study suggests that coherent higher-level information integration can overcome misalignment and has implications for understanding and potentially guiding discourse in polarized environments.

Abstract

The increasing polarization in democratic societies is an emergent outcome of political opinion dynamics. Yet, the fundamental mechanisms behind the formation of political opinions, from individual beliefs to collective consensus, remain unknown. Understanding that a causal mechanism must account for both bottom-up and top-down influences, we conceptualize political opinion dynamics as hierarchical coarse-graining, where microscale opinions integrate into a macro-scale state variable. Using the CODA (Continuous Opinions Discrete Actions) model, we simulate Bayesian opinion updating, social identity-based information integration, and migration between social identity groups to represent higher-level connectivity. This results in coarse-graining across micro, meso, and macro levels. Our findings show that higher-level connectivity shapes information integration, yielding three regimes: independent (disconnected, local convergence), parallel (fast, global convergence), and iterative (slow, stepwise convergence). In the iterative regime, low connectivity fosters transient diversity, indicating an informed consensus. In all regimes, time-scale separation leads to downward causation, where agents converge on the aggregate majority choice, driving consensus. Critically, any degree of coherent higher-level information integration can overcome misalignment via global downward causation. The results highlight how emergent properties of the causal mechanism, such as downward causation, are essential for consensus and may inform more precise investigations into polarized political discourse.

Figures (11)

• Figure 1: The hierarchical coarse-graining of preferred choices from agent to global level is shown on the left, while the process of upward causation in the hierarchical coarse-graining scheme is shown on the right
• Figure 2: Activation barrier (AB) At initialization, the agent’s internal choice distribution consists of six units of information (left panel), the AB is low. As time goes by, the agent integrates information and the AB becomes higher. C1-C2 represent choice 1 and 2 respectively
• Figure 3: Graphical representation of agents' choices on issues Agents evaluate the strength of each choice and express the one with the highest strength
• Figure 4: Flow diagram representing algorithm of the interactions between agents. Note that whether Ignoring is ON or OFF is a parameter of simulation (fixed for given run)
• Figure 5: Independent information integration regime. Results shown are means of 10 simulations per parameter set. PDL = 0; Strength of influence = 20; multi-issue discourse = 20; and ignore is ON or OFF (filled and hollow points). 2, 6, or 10 labels (color and shape-coded points); 1, 5, and 10 issues (rows); and 2, 5 or 10 choices (columns)