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  2. Filter bubble - Wikipedia

    en.wikipedia.org/wiki/Filter_bubble

    A study by data scientists at Facebook found that users have one friend with contrasting views for every four Facebook friends that share an ideology. [53] [54] No matter what Facebook's algorithm for its News Feed is, people are more likely to befriend/follow people who share similar beliefs. [53]

  3. 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.

  4. Facebook Graph Search - Wikipedia

    en.wikipedia.org/wiki/Facebook_Graph_Search

    Facebook Graph Search feature. Facebook Graph Search was a semantic search engine that Facebook introduced in March 2013. It was designed to give answers to user natural language queries rather than a list of links. [1] The name refers to the social graph nature of Facebook, which maps the relationships among users.

  5. Facebook - Wikipedia

    en.wikipedia.org/wiki/Facebook

    For example, a Facebook user can link their email account to their Facebook to find friends on the site, allowing the company to collect the email addresses of users and non-users alike. [216] Over time, countless data points about an individual are collected; any single data point perhaps cannot identify an individual, but together allows the ...

  6. Six degrees of separation - Wikipedia

    en.wikipedia.org/wiki/Six_degrees_of_separation

    Facebook's data team released two papers in November 2011 which document that amongst all Facebook users at the time of research (721 million users with 69 billion friendship links) there is an average distance of 4.74. [36] [29] Probabilistic algorithms were applied on statistical metadata to verify the accuracy of the measurements. [37]

  7. You influence recommendation algorithms just as much as ... - AOL

    www.aol.com/influence-recommendation-algorithms...

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  8. 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 ...

  9. Algorithmic curation - Wikipedia

    en.wikipedia.org/wiki/Algorithmic_curation

    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 .