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My Senior Thesis

Bias Balance.webp

Unveiling Algorithmic Bias: Analyzing Gender and Race Disparities in YouTube’s Recommendation System

This thesis examines gender and race biases in YouTube's recommendation algorithm and their impact on content discovery and engagement across different demographic groups. The analysis reveals that the algorithm often favors content from males and white creators, leading to underrepresentation and limited opportunities for diverse creators.
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