Factual knowledge can reduce attitude polarization

Abstract

It is commonly argued that factual knowledge about a political issue increases attitude polarization due to politically motivated reasoning. By this account, individuals ignore counter-attitudinal facts and direct their attention to pro-attitudinal facts; reject counter-attitudinal facts when directly confronted with them; and use pro-attitudinal facts to counterargue, all making them more polarized. The observation that more knowledgeable partisans are often more polarized is widely taken as support for this account. Yet these data are only correlational. Here, we directly test the causal effect of increasing issue-relevant knowledge on attitude polarization. Specifically, we randomize whether N = 1,011 participants receive a large, credible set of both pro- and counter-attitudinal facts on a contentious political issue - gun control - and provide a modest incentive for them to learn this information. We find evidence that people are willing to engage with and learn policy-relevant facts both for and against their initial attitudes; and that this increased factual knowledge shifts individuals towards more moderate policy attitudes, a durable effect that is still visible after one month. Our results suggest that the impact of directionally motivated reasoning on the processing of political information might be more limited than previously thought.

Fig. 1. The figure shows time data for participants in the experimental condition.

The left panel shows a density plot of the time spent (in log seconds) on politically neutral gun-control modules (teal) versus politically valenced gun-control modules (red). Each dashed colored line indicates the mean of the respective group. The right panel shows a density plot of log times for pro-attitudinal (gray) and counter-attitudinal modules (purple). Each dashed colored line indicates the mean of the respective group.

Fig. 2. Density plots.

The left panel shows a density plot of the helpfulness ratings given to politically neutral gun-control modules (teal) versus politically valenced gun-control modules (red). The black dashed line indicates the scale midpoint and the colored dashed lines indicate the mean of the respective group. The right panel shows a density plot of the ratings given to counter-attitudinal (purple) and pro-attitudinal modules (gray). Again, the black dashed line indicates the scale midpoint and the colored dashed lines indicate the mean of the respective group.

Fig. 3. Effect of treatment on gun-control knowledge, Wave 1.

Violin plots (left) show distributions, interquartile ranges, and medians; bar graphs (right) show means with 95% CIs, overlaid with raw data. Both plots represent the full sample of participants, N = 1011.

Fig. 4. Effect of treatment on each gun control knowledge category in Wave 1, by pre-treatment gun control attitude.

The left panel looks at politically neutral facts by both groups (control and treatment). The center panel looks at both political fact categories, among those who identified as pro-gun control pre-treatment. The right panel looks at both political fact categories, among those who identified as anti-gun control pre-treatment. Bars show means with 95% CIs, overlaid with raw data. All three plots represent the sample of participants who indicated having a pre-treatment position on gun control (n = 926).

Fig. 5. Average treatment effects on the three attitudinal and one affective outcome are plotted on the left (black for Wave 1, purple for Wave 2).

Higher scores indicate greater movement in the opposing direction. 90, 95, and 99% CIs are depicted via line width, central dot indicates the average treatment effect. The right panel depicts density plots showing the distribution of each outcome on the left panel (black for Wave 1, purple for Wave 2), split by treatment (darker color) and control (lighter color) n = 1008.