The Prosocial Ranking Challenge: Reducing Polarization on Social Media without Sacrificing Engagement
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arXiv
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| Auteurs principaux: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Preprint |
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2026
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| author | Stray, Jonathan Baker, Ian Beknazar-Yuzbashev, George Budak, Ceren Kamin, Julia Rutherford, Kylan Stalinski, Mateusz Acosta, Tin Bail, Chris Bernstein, Michael Brandt, Mark Bruckman, Amy Chhabra, Anshuman De, Soham Duskin, Kayla Fish, Sara Goldberg, Beth Guess, Andy Hadfield-Menell, Dylan Haroon, Muhammed Hossain, Safwan Inzlicht, Michael Jain, Gauri Jiang, Yanchen Landry, Alexander P. Lelkes, Yph Lu, Hongfan Mason, Peter McCoy, Jennifer Milli, Smitha Resnick, Paul Saltz, Emily Saveski, Martin Schirch, Lisa Spohn, Max Srinivasan, Siddarth Tatore, Alexis Thorburn, Luke Tucker, Joshua A. Willer, Robb Wojcieszak, Magdalena Wüthrich, Manuel Zheng, Sylvan |
| author_facet | Stray, Jonathan Baker, Ian Beknazar-Yuzbashev, George Budak, Ceren Kamin, Julia Rutherford, Kylan Stalinski, Mateusz Acosta, Tin Bail, Chris Bernstein, Michael Brandt, Mark Bruckman, Amy Chhabra, Anshuman De, Soham Duskin, Kayla Fish, Sara Goldberg, Beth Guess, Andy Hadfield-Menell, Dylan Haroon, Muhammed Hossain, Safwan Inzlicht, Michael Jain, Gauri Jiang, Yanchen Landry, Alexander P. Lelkes, Yph Lu, Hongfan Mason, Peter McCoy, Jennifer Milli, Smitha Resnick, Paul Saltz, Emily Saveski, Martin Schirch, Lisa Spohn, Max Srinivasan, Siddarth Tatore, Alexis Thorburn, Luke Tucker, Joshua A. Willer, Robb Wojcieszak, Magdalena Wüthrich, Manuel Zheng, Sylvan |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_19626 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | The Prosocial Ranking Challenge: Reducing Polarization on Social Media without Sacrificing Engagement Stray, Jonathan Baker, Ian Beknazar-Yuzbashev, George Budak, Ceren Kamin, Julia Rutherford, Kylan Stalinski, Mateusz Acosta, Tin Bail, Chris Bernstein, Michael Brandt, Mark Bruckman, Amy Chhabra, Anshuman De, Soham Duskin, Kayla Fish, Sara Goldberg, Beth Guess, Andy Hadfield-Menell, Dylan Haroon, Muhammed Hossain, Safwan Inzlicht, Michael Jain, Gauri Jiang, Yanchen Landry, Alexander P. Lelkes, Yph Lu, Hongfan Mason, Peter McCoy, Jennifer Milli, Smitha Resnick, Paul Saltz, Emily Saveski, Martin Schirch, Lisa Spohn, Max Srinivasan, Siddarth Tatore, Alexis Thorburn, Luke Tucker, Joshua A. Willer, Robb Wojcieszak, Magdalena Wüthrich, Manuel Zheng, Sylvan Social and Information Networks Information Retrieval J.4; H.3.3; K.4.2 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. |
| title | The Prosocial Ranking Challenge: Reducing Polarization on Social Media without Sacrificing Engagement |
| topic | Social and Information Networks Information Retrieval J.4; H.3.3; K.4.2 |
| url | https://arxiv.org/abs/2603.19626 |