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Found 4 papers, 4 papers with code
Exploring Social Choice Mechanisms for Recommendation Fairness in SCRUF
Fairness problems in recommender systems often have a complexity in practice that is not adequately captured in simplified research formulations.
Auditing YouTube's Recommendation Algorithm for Misinformation Filter Bubbles
We also observe a sudden decrease of misinformation filter bubble effect when misinformation debunking videos are watched after misinformation promoting videos, suggesting a strong contextuality of recommendations.
Monant Medical Misinformation Dataset: Mapping Articles to Fact-Checked Claims
It also contains 573 manually and more than 51k automatically labelled mappings between claims and articles.
An Audit of Misinformation Filter Bubbles on YouTube: Bubble Bursting and Recent Behavior Changes
We present a study in which pre-programmed agents (acting as YouTube users) delve into misinformation filter bubbles by watching misinformation promoting content (for various topics).
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