Influence of symbolic content on recommendation bias: analyzing YouTube’s algorithm during Taiwan’s 2024 election
Abstract This study investigates the role of symbolic content, including social, cultural, and political imagery, in shaping algorithmic biases within YouTube’s recommendation system, using the 2024 Taiwanese presidential election as a case study. Leveraging classification methodology and a dataset...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2025-06-01
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| Series: | Applied Network Science |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s41109-025-00713-y |
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