An Online experiment during the 2020 US–Iran crisis shows that exposure to common enemies can increase political polarization

Abstract

A longstanding theory indicates that the threat of a common enemy can mitigate conflict between members of rival groups. We tested this hypothesis in a pre-registered experiment where 1670 Republicans and Democrats in the United States were asked to complete an online social learning task with a bot that was labeled as a member of the opposing party. Prior to this task, we exposed respondents to primes about (a) a common enemy (involving Iran and Russia); (b) a patriotic event; or (c) a neutral, apolitical prime. Though we observed no significant differences in the behavior of Democrats as a result of priming, we found that Republicans—and particularly those with very strong conservative views—were significantly less likely to learn from Democrats when primed about a common enemy. Because our study was in the field during the 2020 Iran Crisis, we were able to further evaluate this finding via a natural experiment—Republicans who participated in our study after the crisis were even less influenced by the beliefs of Democrats than those Republicans who participated before this event. These findings indicate common enemies may not reduce inter-group conflict in highly polarized societies, and contribute to a growing number of studies that find evidence of asymmetric political polarization in the United States. We conclude by discussing the implications of these findings for research in social psychology, political conflict, and the rapidly expanding field of computational social science.

Escape from fraught states in a coordination game

“…Figure 4 shows an average of all successful but substantially fraught trajectories from the Hierarchy rounds of the Confirmatory Lab Data Set. 5 To make this figure, we first rasterized all rounds so they had the same number (1500) of equally spaced time steps and then divided discrete time by 1500 so it ranged from 0 to 1. Moreover, if necessary, the sign of each player's position was flipped a posteriori so that every dataset converged on the consensus corner {1} 7 .…”

“…Corresponding research generally strives to understand its causes, often with an eye to avoiding or discouraging it. This perspective holds across a number of naturalistic [1][2][3], experimental [4][5][6], computational and/or mathematical [7][8][9][10][11], and review [12,13] studies.…”

Escape from fraught states in a coordination game

“…Corresponding research generally strives to understand its causes, often with an eye to avoiding or discouraging it. This perspective holds across a number of naturalistic [1][2][3], experimental [4][5][6], computational [7][8][9], mathematical [10], and cross-cutting [11] studies.…”

“…(4) An averaging analysis of the slider position time histories showed a characteristic profile which robustly appeared across distinct batches of runs. (5) We investigated several computational models, one of which produced an averaging profile similar to that of the humans. This optimal model supports a speculation that Agreement is akin to energy in a stochastic physical system; fraughtness is a form of metastability and groups escape it by waiting long enough for noise to dislodge the group from a higher-energy state into a lower one.…”

“…Fig.1a. )4 In the Ring topology, all players are self-connected and also connected to one another in a single loop 5. In the Star topology, all players are self-connected, and a single central player is connected to every other player.April 24, 2023 5/25…”