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The Mutual Domestication of Users and Algorithmic Recommendations on Netflix

机译:Netflix上的用户相互驯化和算法建议

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This article examines the mutual domestication of users and recommendation algorithms on Netflix. Based on 25 interviews with users and an inductive analysis of their practices and profiles on the platform, we discuss five dynamics through which thismutual domestication occurs: personalization, or the ways in which individualized relationships between users and the platform are bui how algorithmic recommendations are integrated into a matrix of cultural codes; the rituals through which they are incorporated into spatial and temporal processes in daily life; the resistance to various aspects of Netflix as a form to enact agency; and the conversion or transformation of the private consumption of the platform into a public issue. The conclusion elaborates on the theoretical and analytical implications of this approach, to rethink the relationship between algorithms and culture.
机译:本文研究了Netflix上用户的相互驯化和推荐算法。基于对用户的25次采访以及对他们在平台上的行为和概况的归纳分析,我们讨论了这种相互驯化发生的五种动力:个性化,或建立用户与平台之间的个性化关系的方式;如何将算法建议整合到文化规范矩阵中;将这些仪式纳入日常生活中的时空过程的仪式;抵制Netflix作为制定代理机构形式的各个方面;以及将平台的私人消费转化为公共问题。结论详细阐述了此方法的理论和分析含义,以重新考虑算法与文化之间的关系。

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