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The study noted that YouTube’s recommendation algorithm “drives 70% of all video views.” ...
YouTube has faced criticism over aspects of its operations, [1] its recommendation algorithms perpetuating videos that promote conspiracy theories and falsehoods, [2] hosting videos ostensibly targeting children but containing violent or sexually suggestive content involving popular characters, [3] videos of minors attracting pedophilic ...
Algorithmic radicalization is the concept that recommender algorithms on popular social media sites such as YouTube and Facebook drive users toward progressively more extreme content over time, leading to them developing radicalized extremist political views. Algorithms record user interactions, from likes/dislikes to amount of time spent on ...
YouTube's content recommendation algorithm is designed to keep the user engaged as long as possible, which Roose calls the "rabbit hole effect". [5] The podcast features interviews with a variety of people involved with YouTube and the "rabbit hole effect". [6] For instance, in episode four Roose interviews Susan Wojcicki—the CEO of YouTube. [2]
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The researchers then took note of the top 10 recommendations in the “Up Next” panel to the right of the video. They carried out the simulation 100 times, analyzing 1,000 videos in total.
Algorithmic curation is the selection of online media by recommendation algorithms and personalized searches. Examples include search engine and social media products [ 1 ] such as the Twitter feed , Facebook 's News Feed , and the Google Personalized Search .
The user based top-N recommendation algorithm uses a similarity-based vector model to identify the k most similar users to an active user. After the k most similar users are found, their corresponding user-item matrices are aggregated to identify the set of items to be recommended.