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Investigating Bias in YouTube Recommendations: Emotion, Morality, and Network Dynamics in China-Uyghur Content
2 references·1 citing·12 second hop
Investigating Bias in YouTube Recommendations: Emotion, Morality, and Network Dynamics in China-Uyghur Content (2024)Investigating Bias in YouTube Recommendat…Understanding Echo Chambers and Filter Bubbles: The Impact of Social Media on Diversification and Partisan Shifts in News Consumption (2020)Understanding Echo Chambers a…Emotion Analysis of Songs Based on Lyrical and Audio Features (2015)Emotion Analysis of Songs Bas…Unveiling Bias in YouTube Shorts: Analyzing Thumbnail Recommendations and Topic Dynamics (2024)Unveiling Bias in YouTube Sho…Core affect, prototypical emotional episodes, and other things called emotion: Dissecting the elephant. (1999)A comparison of dimensional models of emotion: Evidence from emotions, prototypical events, autobiographical memories, and words (2009)“The Girl Next Door”: A Semantic Lyrical Analysis of Zahara’s Songs “Destiny” and “Rise Again” (2023)Structural Holes (1992)Confirmation Bias: A Ubiquitous Phenomenon in Many Guises (1998)Social Media and Fake News in the 2016 Election (2017)A systematic review of worldwide causal and correlational evidence on digital media and democracy (2022)Artificial Intelligence and Democracy: A Conceptual Framework (2023)Generative AI and its Transformative Value for Digital Platforms (2025)China’s Strategy in the South China Sea (2011)PRC Assertiveness in the South China Sea: Measuring Continuity and Change, 1970–2015 (2021)Analyzing Bias in Recommender Systems: A Comprehensive Evaluation of YouTube's Recommendation Algorithm (2023)
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References

  • 2020Understanding Echo Chambers and Filter Bubbles: The Impact of Social Media on Diversification and Partisan Shifts in News Consumption430 cited
  • 2015Emotion Analysis of Songs Based on Lyrical and Audio Features53 cited

Cited by

  • 2024Unveiling Bias in YouTube Shorts: Analyzing Thumbnail Recommendations and Topic Dynamics10 cited

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