● Covered by 2 sources · 2 reportsMedium impact2 negative
Study finds X's algorithm prioritizes engagement, shows more 'ragebait' to Democrats
Key points
- X's algorithm optimizes for engagement on the 'For You Page'.
- The algorithm serves more 'ragebait' content to self-identified Democrats.
- Study involved 715 active X users in September and October 2024.
- Researchers collected user values and observed engagement with posts.
- Study published in PNAS.
- Ziv Epstein, a Stanford researcher, is one of the paper's authors.
Algorithm Prioritizes Engagement
A study published in the Proceedings of the National Academy of Sciences (PNAS) titled "Value misalignment of X’s feed algorithm is a reflection of value tensions in engagement" found that X's algorithm prioritizes engagement above other factors when generating a user's 'For You Page'. This optimization for engagement influences the type of content users encounter on the platform.
Increased 'Ragebait' for Democrats
The study also revealed that X's algorithm serves more 'ragebait' content to users who identify as Democrats. The exact reasons for this specific targeting are not yet clear, but it indicates a differential content experience based on political alignment.
Study Methodology
Researchers recruited 715 active X users in September and October 2024, forming a nationally representative sample matched on ethnicity, gender, and partisanship. Participants installed a browser extension to collect data from their 'For You Page' and Following feeds. The study also involved collecting a 'values inventory' from volunteers using the Schwartz Theory of Basic Values, which included 19 points corresponding to features like 'tolerance' and 'dominance', alongside self-reported political alignments.
Implications for Information Consumption
Ziv Epstein, a co-author of the paper and postdoctoral researcher at Stanford University, stated that the study was observational and aimed to prompt questions about social media feed design and its impact. He emphasized the significant power of social media algorithms in shaping information consumption and the lack of transparency regarding their operations and implications for civil society.
Updates
- Study published in PNAS.
- Ziv Epstein, a Stanford researcher, is one of the paper's authors.
✨ This summary was generated by AI from the outlets' reporting listed below. It is not independently verified and may contain errors — check the original sources. How BrevFeed works →
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How outlets covered it
A study published in PNAS indicates that X's algorithm amplifies "ragebait" content to increase engagement, with a disproportionate impact on users identifying as Democrats. The research suggests the algorithm prioritizes content that provokes outrage, leading to a feedback loop where users are shown more infuriating posts.
A new study published in PNAS found that X's algorithm prioritizes engagement, leading to more 'ragebait' content being shown, particularly to users who identify as Democrats. This research highlights how social media algorithms shape information consumption with limited transparency.