Netflix recommends : algorithms, film choice, and the history of taste /

"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 rec...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Frey, Mattias (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Oakland, California : University of California Press, [2021]
Temas:
Netflix (Firm)
Streaming video > Social aspects > United States.
Recommender systems (Information filtering) > Social aspects.
Vidéo en continu > Aspect social > États-Unis.
Systèmes de recommandation (Filtrage d'information) > Aspect social.
SOCIAL SCIENCE / Media Studies
United States.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Introduction
  • Why we need film and series suggestions
  • How algorithmic recommender systems work
  • Cracking the code, part I : developing Netflix's recommendation algorithms
  • Cracking the code, part II : unpacking Netflix's myth of big data
  • How real people choose films and series
  • Afterword : robot critics vs. human experts
  • Appendix : designing the empirical audience study.

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