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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.
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Instagram's head says engagement falls by half without the algorithm
Instagram head Adam Mosseri says disabling ranked feeds cuts engagement up to 50%, amid Australian legislation that would force platforms to offer algorithm opt-outs.
Meta's Adam Mosseri told an Australian press briefing that users switching to chronological feeds see engagement fall by as much as 50% and satisfaction drop sharply, arguing ranked feeds deliver a better experience. Australia's draft Digital Duty of Care bill would require platforms to prompt users to disable algorithmic ranking. The EU's Digital Services Act Article 38 has required very large platforms to offer a non-profiling feed option since 2023, with modest adoption. Meta also faces a social media harms trial in which Instagram's addictive design is at issue.
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Quantifying the Engagement Trap: Impact of Short-form Video Recommender Systems on Users with ADHD
A 302-participant study finds engagement-optimized short-form video recommenders cause disproportionate time blindness and distress for users with ADHD.
Researchers ran a stratified Prolific study with 302 participants comparing short-form video recommendation experiences with and without ADHD. Participants with ADHD reported significantly higher time blindness, post-usage regret, and emotional distress despite perceiving recommendations as similarly relevant. The paper proposes neurodiversity-aware, human-centered design interventions to mitigate these algorithmic harms.
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