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Netflix Recommends : Algorithms, Film Choice, and the History of Taste

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Title: Netflix Recommends : Algorithms, Film Choice, and the History of Taste
Description: Algorithmic recommender systems, deployed by media companies to suggest content based on users'viewing histories, have inspired hopes for personalized, curated media but also dire warnings of filter bubbles and media homogeneity. Curiously, both proponents and detractors assume that recommender systems for choosing films and series are novel, effective, and widely used. Scrutinizing the world's most subscribed streaming service, Netflix, this book challenges that consensus. Investigating real-life users, marketing rhetoric, technical processes, business models, and historical antecedents, Mattias Frey demonstrates that these choice aids are neither as revolutionary nor as alarming as their celebrants and critics maintain—and neither as trusted nor as widely used. Netflix Recommends brings to light the constellations of sources that real viewers use to choose films and series in the digital age and argues that although some lament AI's hostile takeover of humanistic cultures, the thirst for filters, curators, and critics is stronger than ever.
Authors: Mattias Frey
Resource Type: eBook.
Subjects: Recommender systems (Information filtering)--Social aspects, Streaming video--Social aspects--United States
Categories: PERFORMING ARTS / Television / History & Criticism, COMPUTERS / Internet / General, SOCIAL SCIENCE / Media Studies
Database: eBook Collection (EBSCOhost)
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  Data: Algorithmic recommender systems, deployed by media companies to suggest content based on users'viewing histories, have inspired hopes for personalized, curated media but also dire warnings of filter bubbles and media homogeneity. Curiously, both proponents and detractors assume that recommender systems for choosing films and series are novel, effective, and widely used. Scrutinizing the world's most subscribed streaming service, Netflix, this book challenges that consensus. Investigating real-life users, marketing rhetoric, technical processes, business models, and historical antecedents, Mattias Frey demonstrates that these choice aids are neither as revolutionary nor as alarming as their celebrants and critics maintain—and neither as trusted nor as widely used. Netflix Recommends brings to light the constellations of sources that real viewers use to choose films and series in the digital age and argues that although some lament AI's hostile takeover of humanistic cultures, the thirst for filters, curators, and critics is stronger than ever.
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      – Code: 384.5554
        Scheme: ddc
        Type: prePub
    Languages:
      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: Recommender systems (Information filtering)--Social aspects
        Type: general
      – SubjectFull: Streaming video--Social aspects--United States
        Type: general
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      – TitleFull: Netflix Recommends : Algorithms, Film Choice, and the History of Taste
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            – D: 01
              M: 01
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              Y: 2021
            – D: 27
              M: 10
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