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Analyzing YouTube Kids’ recommendation algorithm for content diversity
Adams, Olaf (2025) Analyzing YouTube Kids’ recommendation algorithm for content diversity.
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| Abstract: | In this paper, the behavior of the YouTube Kids recommendation algorithm and its potential influence on the formation of content filter bubbles is investigated. YouTube Kids videos are collected by a Playwright pipeline, which are then included in a recommendation tree. The results show that the entropy remains stable along the average recommendation sequence, going against the claim of the algorithm pushing users into filter bubbles. Transition matrices do showcase potential biases in the algorithm towards recommending certain content, particularly videos in the ’Cartoons’ category. The matrices also show high self-transition probabilities, indicating a high likelihood for the algorithm to recommend the same genre of video multiple times in a row. These findings suggest moderate content diversity on the platform, but also call for action to improve the algorithms’ behavior to positively affect children’s exposure to a variety of content. |
| Item Type: | Essay (Bachelor) |
| Faculty: | EEMCS: Electrical Engineering, Mathematics and Computer Science |
| Subject: | 54 computer science |
| Programme: | Computer Science BSc (56964) |
| Link to this item: | https://purl.utwente.nl/essays/107326 |
| Export this item as: | BibTeX EndNote HTML Citation Reference Manager |
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