X's Algorithm Feeds Off Ragebait and Impacts Democrats More, Study Finds
A PNAS study of 715 X users finds the platform's engagement-optimizing algorithm amplifies value-misaligned ragebait, affecting self-identified Democrats more.
A study published in the Proceedings of the National Academy of Sciences used browser extension data from 715 U.S. X users, recruited in September and October 2024, to compare self-reported values with the content the For You feed amplified. It found that replying to posts—only 6.8% of observed interactions—disproportionately shapes the engagement-optimizing algorithm, creating runaway feedback loops of value-misaligned ragebait that were more pronounced for self-identified Democrats. Co-author Ziv Epstein, a postdoctoral researcher at Stanford University, said the observational work is intended to spur debate on algorithm transparency and user control over feeds.
- Replying was only 6.8% of interactions but disproportionately shaped what the algorithm served users
- Self-identified Democrats received more value-misaligned ragebait, creating a runaway feedback loop
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- X
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- Stanford UniversityPNAS
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- United States
From the original article
5 min read at 404media.co
X’s algorithm learns what you hate and shows you more of it, according to a new study just published in the Proceedings of the National Academy of Sciences (PNAS). The paper, titled Value misalignment of X’s feed algorithm is a reflection of value tensions in engagement , found that the site’s algorithm prioritized engagement above all else when it generated a user’s For You Page.
By Matthew Gault · 404media.co
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