Perspective-taking to Reduce Affective Polarization on Social Media
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Abstract (arXiv)
The intensification of affective polarization worldwide has raised new questions about how social media platforms might be further fracturing an already-divided public sphere. As opposed to ideological polarization, affective polarization is defined less by divergent policy preferences and more by strong negative emotions towards opposing political groups, and thus arguably poses a formidable threat to rational democratic discourse. We explore if prompting perspective-taking on social media platforms can help enhance empathy between opposing groups as a first step towards reducing affective polarization. Specifically, we deploy a randomized field experiment through a browser extension to 1,611 participants on Twitter, which enables participants to randomly replace their feeds with those belonging to accounts whose political views either agree with or diverge from their own. We find that simply exposing participants to "outgroup" feeds enhances engagement, but not an understanding of why others hold their political views. On the other hand, framing the experience in familiar, empathic terms by prompting participants to recall a disagreement with a friend does not affect engagement, but does increase their ability to understand opposing views. Our findings illustrate how social media platforms might take simple steps that align with business objectives to reduce affective polarization.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 Oct 2021.
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Citing papers per year: 2023: 2; 2024: 2; 2025: 0; 2026: 1.
5 papers.
- 2023Embedding Democratic Values into Social Media AIs via Societal Objective Functionscited by 25
- 2023Do Differences in Values Influence Disagreements in Online Discussions?cited by 15
- 2024Reranking partisan animosity in algorithmic social media feeds alters affective polarizationcited by 7
- 2024The Computational Anatomy of Humility: Modeling Intellectual Humility in Online Public Discoursecited by 3
- 2026A Natural Language Agentic Approach to Study Affective Polarizationcited by 2
- 2026A Natural Language Agentic Approach to Study Affective Polarization3 Mar 2026
- 2024Reranking partisan animosity in algorithmic social media feeds alters affective polarization22 Nov 2024
- 2024The Computational Anatomy of Humility: Modeling Intellectual Humility in Online Public Discourse19 Oct 2024
- 2023Do Differences in Values Influence Disagreements in Online Discussions?24 Oct 2023
- 2023Embedding Democratic Values into Social Media AIs via Societal Objective Functions26 Jul 2023