Preventing extreme polarization of political attitudes

Abstract

Extreme polarization can undermine democracy by making compromise impossible and transforming politics into a zero-sum game. "Ideological polarization"-the extent to which political views are widely dispersed-is already strong among elites, but less so among the general public [N. McCarty, Polarization: What Everyone Needs to Know, 2019, pp. 50-68]. Strong mutual distrust and hostility between Democrats and Republicans in the United States, combined with the elites' already strong ideological polarization, could lead to increasing ideological polarization among the public. The paper addresses two questions: 1) Is there a level of ideological polarization above which polarization feeds upon itself to become a runaway process? 2) If so, what policy interventions could prevent such dangerous positive feedback loops? To explore these questions, we present an agent-based model of ideological polarization that differentiates between the tendency for two actors to interact ("exposure") and how they respond when interactions occur, positing that interaction between similar actors reduces their difference, while interaction between dissimilar actors increases their difference. Our analysis explores the effects on polarization of different levels of tolerance to other views, responsiveness to other views, exposure to dissimilar actors, multiple ideological dimensions, economic self-interest, and external shocks. The results suggest strategies for preventing, or at least slowing, the development of extreme polarization.

Keywords: agent-based models; democracy; ideology; opinion change; political polarization.

Fig. 1.

The effects of tolerance (T). Polarization of the population’s ideological positions over time when varying tolerance over the range $T=0.05,0.15,\dots ,0.95$ (dark blue to yellow). Low tolerance ($T\le 0.25$) leads to extreme polarization, intermediate tolerance ($0.35\le T\le 0.45$) leads to small but nonzero polarization, and high tolerance ($T\ge 0.55$) leads to convergence.

Fig. 2.

With intermediate tolerance, can the center hold? Snapshots of the population’s one-dimensional ideological positions (D1) over time, shown as histograms for the $T=0.25$ and $T=0.35$ runs shown in Fig. 1. (A) Initially, the 100 actors are normally distributed with mean 0.5 and SD $\sigma =0.2$. (B) At step 100,000, the $T=0.25$ run forms a moderate majority of $\sim$80 actors flanked by extreme groups at the far left and far right of $\sim$10 actors each. (C) The extreme groups grow steadily as the moderate majority dissolves. (D) After 2,500,000 steps or—using our estimation of one interaction per actor per day—about 70 y, all actors have converged to the extremes in equal proportions. (E–H) The $T=0.35$ run forms and maintains a larger moderate majority ($\sim$90 actors) that remains stable over all 2,500,000 steps. See Movie S1 for animations.

Fig. 3.

The effects of responsiveness (R) as a function of tolerance (T). Average polarization of the population’s ideological positions after 1,000,000 steps, averaged over 20 iterations for each $\left(T,R\right)$ pair. $T$ and $R$ are both varied over the range $0.05,0.10,\dots ,1.0$. There is a phase change from extreme polarization (yellow) with low $T$ to convergence (dark blue) with high $T$. The phase change is largely independent of $R$. A and B indicate the $T=0.25$ and $T=0.35$ cases shown in Fig. 2 on the boundary of the phase change.

Fig. 4.

The effects of exposure (E) as a function of tolerance (T). Average polarization of the population’s ideological positions after 2,000,000 steps, averaged over 20 iterations for each $\left(T,E\right)$ pair. Tolerance is varied over $T=0.05,0.1,\dots ,1.0$, and exposure is varied over $E=0.05,0.1,\dots ,0.5$.

Fig. 5.

The effects of exposure (E) for intermediate tolerance (T). Polarization of the population’s ideological positions over time when $T=0.3$ is fixed and exposure is varied over the range $E=0.05,0.1,\dots ,0.5$ (dark blue to yellow). $E\le 0.1$ leads to a stable moderate majority flanked by repulsive extremists, while $E\ge 0.15$ leads to rapid polarization.

Fig. 6.

Avoiding maximum polarization with low exposure (E). Polarization of the population’s ideological positions over time when exposure on the first ideological dimension is fixed at $E_1=0.1$ and exposure on the second ideological dimension is varied over $E_2=0.05,0.1,\dots ,0.5$ (dark blue to yellow). (Insets) Final configurations of the population after 2,500,000 steps for the $E_2=0.4$ (Top) and $E_2=0.05$ (Bottom) runs as a 2D histogram whose colors indicate concentrations of actors on a log-scale. See Movie S3 for animations.

Fig. 7.

The effects of economic self-interest (P). Polarization of the population’s ideological positions over time with varying levels of economic self-interest, $P=0\%,1\%,\dots ,10\%$ (dark blue to yellow) that an actor will be attracted to its preferred (initial) position. (Left Inset) The initial normal distribution of actors’ ideological positions, which also represent their preferred positions when acting in self-interest. (Right Insets) Final configurations of the population after 2,500,000 steps for $P=0\%$, $1\%$, and $10\%$. See Movie S4 for animations.

Fig. 8.

The effects of external shock strength ($\mathrm{\Delta }$) on repulsive extremists. (A) Polarization of the population’s ideological positions over time with external shocks of varying strengths $\mathrm{\Delta }=0.0,0.05,\dots ,0.8$ (dark blue to yellow) introduced at step 500,000. (B) Snapshots of the population’s ideological positions as histograms for the $\mathrm{\Delta }=0.1$, 0.4, and 0.8 runs just before the shock (step 500,000; Left), shortly after the shock (step 501,000; Middle), and in the final configuration (step 2,500,000; Right). See Movie S5 for animations.

Fig. 9.

The effects of external shock, by time and strength. Average polarization of the population’s ideological positions after 2,000,000 steps, averaged over 20 iterations for each $\left(\mathrm{\Delta },\text{step}\right)$ pair. Shocks vary in strength over $\mathrm{\Delta }=0.0,0.05,\dots ,0.8$ and are introduced at steps 100,000, 200,000, $\dots$, 900,000.