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  2. List of Facebook features - Wikipedia

    en.wikipedia.org/wiki/List_of_Facebook_features

    [185] In 2009, Facebook added the feature to tag certain friends (or groups, etc.) within one's status update by adding an @ character before their name, turning the friend's name into a link to their profile and including the message on the friend's wall. Tagging has since been updated to recognize friends' names by typing them into a status ...

  3. Feed (Facebook) - Wikipedia

    en.wikipedia.org/wiki/Feed_(Facebook)

    Following surveys of Facebook users, [27] this desire for change will take the form of a reconfiguration of the News Feed algorithms in order to: Prioritize content of family members and friends (Mark Zuckerberg January 12, Facebook: [28] "The first changes you'll see will be in News Feed, where you can expect to see more from your friends, family and groups".)

  4. 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 ...

  5. 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 .

  6. 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.

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

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

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  8. 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.

  9. Facebook like button - Wikipedia

    en.wikipedia.org/wiki/Facebook_like_button

    The like button is a feature of social networking service Facebook, where users can like content such as status updates, comments, photos and videos, links shared by friends, and advertisements. The feature was activated February 9, 2009. [ 2 ]