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  2. YouTube's algorithm more likely to recommend users ... - AOL

    www.aol.com/news/youtube-algorithm-more-likely...

    The study noted that YouTube’s recommendation algorithm “drives 70% of all video views.” ... “YouTube’s recommendation system is trained to raise high-quality content on the home page ...

  3. Algorithmic radicalization - Wikipedia

    en.wikipedia.org/wiki/Algorithmic_radicalization

    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 ...

  4. Recommender system - Wikipedia

    en.wikipedia.org/wiki/Recommender_system

    A recommender system (RecSys), or a recommendation system (sometimes replacing system with terms such as platform, engine, or algorithm), is a subclass of information filtering system that provides suggestions for items that are most pertinent to a particular user.

  5. Cold start (recommender systems) - Wikipedia

    en.wikipedia.org/wiki/Cold_start_(recommender...

    The cold start problem is a well known and well researched problem for recommender systems.Recommender systems form a specific type of information filtering (IF) technique that attempts to present information items (e-commerce, films, music, books, news, images, web pages) that are likely of interest to the user.

  6. Collaborative filtering - Wikipedia

    en.wikipedia.org/wiki/Collaborative_filtering

    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.

  7. Rabbit Hole (podcast) - Wikipedia

    en.wikipedia.org/wiki/Rabbit_Hole_(podcast)

    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]

  8. YouTube algorithm suggests videos about disordered eating to ...

    www.aol.com/youtube-algorithm-suggests-videos...

    YouTube’s algorithm is recommending videos about disordered eating and weight loss to some young teens, a new study says. ... The researchers then took note of the top 10 recommendations in the ...

  9. History of YouTube - Wikipedia

    en.wikipedia.org/wiki/History_of_YouTube

    YouTube has faced criticism over aspects of its operations, including its handling of copyrighted content contained within uploaded videos, [3] its recommendation algorithms perpetuating videos that promote conspiracy theories and falsehoods, [4] hosting videos ostensibly targeting children but containing violent or sexually suggestive content ...