The Mutual Domestication of Users and Algorithmic Recommendations on Netflix

Bibliographic Data

ID12918484
AuthorsIgnacio Siles (0000-0002-9725-8694, Universidad de Costa Rica, corresponding author), Johan Espinoza Rojas (0000-0001-8292-8512, Universidad de Costa Rica), Johan Espinoza-Rojas (School of Communication, Universidad de Costa Rica AP 2060, San Jose, Costa Rica), Adrián Naranjo (Universidad de Costa Rica), María Fernanda Tristán (Universidad de Costa Rica)
Year2019
Publication date2019-07-08
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueCommunication Culture and Critique (JOURNAL)
Journal identifiersISSN: 1753-9137 • E-ISSN: 1753-9129
PublisherOxford University Press (OUP) (PUBLISHER)
DOI10.1093/ccc/tcz025
OpenAlexW2972342321
LanguageEN
Citations received39
References cited11

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 this mutual domestication occurs: personalization, or the ways in which individualized relationships between users and the platform are built; 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

Agency (philosophy · Domestication · Personalization · Recommender system · Social science · Sociology · Transformation (genetics · World Wide Web · Computer Science · Digital Economy and Work Transformation · Innovative Human-Technology Interaction · Sexuality, Behavior, and Technology

Tools

Open DOISci-HubOpen Access