2023/06/27 by Charlotte Brand, Daniel Brady, Tom Stafford · 1 voice
Computer Science · Social Sciences · #Hate Speech and Cyberbullying Detection #Misinformation and Its Impacts
paper · pdf · doi:10.31234/osf.io/2e9wn
openalex publication_date 2023/06/27 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Understanding our ideological opponents is crucial to the effective exchange of arguments and the avoidance of escalation and reduction of conflict. We operationalise the idea of an ‘Ideological Turing Test’ to measure the accuracy with which people represent the arguments of their ideological opponents. Crucially, this offers a behavioural measure of open-mindedness which goes beyond mere self-report. We recruited 200 participants from opposite sides of three topics with potential for polarisation in the UK of the early 2020s (1200 participants total). Participants were asked to provide reasons both for and against their position. Their reasons were then rated by participants from the opposite side. Our criteria for “passing” the test was if an argument was agreed with by opponents to the same extent or higher than arguments made by proponents. We found evidence for high levels of mutual understanding across all three topics. We also found that those who passed were more open-minded towards their opponents, in that they were less likely to rate them as ignorant, immoral or irrational. Our method provides a behavioural measure of open-mindedness and ability to mimic counter-partisan perspectives that goes beyond self-report measures. Our results offer encouragement that, even in highly polarised debates, high levels of mutual understanding persist.