The Prosocial Ranking Challenge: Reducing Polarization on Social Media without Sacrificing Engagement

TL;DR

This study tested alternative social media algorithms during the 2024 US election, finding they can reduce polarization and negative experiences without harming user engagement or well-being.

Contribution

It provides the first direct comparison of multiple ranking algorithms across platforms, demonstrating potential to reduce polarization while maintaining engagement.

Findings

Reduced affective polarization by 0.03 SDs

Decreased Facebook and Reddit usage, increased Twitter usage

No negative impact on well-being or support for violence

Abstract

We report the first direct comparisons of multiple alternative social media algorithms on multiple platforms on outcomes of societal interest. We used a browser extension to modify which posts were shown to desktop social media users, randomly assigning 9,386 users to a control group or one of five alternative ranking algorithms which simultaneously altered content across three platforms for six months during the US 2024 presidential election. This reduced our preregistered index of affective polarization by an average of 0.03 standard deviations (p < 0.05), including a 1.5 degree decrease in differences between the 100 point inparty and outparty feeling thermometers. We saw reductions in active use time for Facebook (-0.37 min/day) and Reddit (-0.2 min/day), but an increase of 0.32 min/day (p < 0.01) for X/Twitter. We saw an increase in reports of negative social media experiences but found no effects on well-being, news knowledge, outgroup empathy, perceptions of and support for partisan violence. This implies that bridging content can improve some societal outcomes without necessarily conflicting with the engagement-driven business model of social media.