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 tru...
This paper explores how audiences engage with Netflix as an intermediary in their digital lives, and...
Objectives The main objectives of this study were to explore the factors which influence whether...
Netflix has shaken up audiovisual industry, but what about academic research? This bibliometric anal...
While a trend of cord-cutting accelerated in the early days of the pandemic, the prevalence of media...
This project proposes a user-focused approach to study the algorithm logic of on-demand apps, using ...
This article examines the mutual domestication of users and recommendation algorithms on Netflix. Ba...
The purpose of this project is going to analyze the data from Netflix. It's going to start with a ge...
The purpose of this project is going to analyze the data from Netflix. It's going to start with a ge...
Algorithms are new cultural intermediaries (Bourdieu, 1984) that shape contemporary cultural experie...
Collaborative filtering algorithms, whose adoption by online recommendation engines has markedly inc...
Following the end of September announcement, the on-demand streaming service Netflix was officially ...
In the last two decades technology companies engaging in surveillance capitalism (gathering data, c...
Technology has evolved a lot from basic to advanced such as Machine learning, deep learning, Interne...
Netflix is considered as a global business invested in strategies of diversification, localisation a...
Recommendation systems are used in hundreds of different services - everywhere from online shopping ...
This paper explores how audiences engage with Netflix as an intermediary in their digital lives, and...
Objectives The main objectives of this study were to explore the factors which influence whether...
Netflix has shaken up audiovisual industry, but what about academic research? This bibliometric anal...
While a trend of cord-cutting accelerated in the early days of the pandemic, the prevalence of media...
This project proposes a user-focused approach to study the algorithm logic of on-demand apps, using ...
This article examines the mutual domestication of users and recommendation algorithms on Netflix. Ba...
The purpose of this project is going to analyze the data from Netflix. It's going to start with a ge...
The purpose of this project is going to analyze the data from Netflix. It's going to start with a ge...
Algorithms are new cultural intermediaries (Bourdieu, 1984) that shape contemporary cultural experie...
Collaborative filtering algorithms, whose adoption by online recommendation engines has markedly inc...
Following the end of September announcement, the on-demand streaming service Netflix was officially ...
In the last two decades technology companies engaging in surveillance capitalism (gathering data, c...
Technology has evolved a lot from basic to advanced such as Machine learning, deep learning, Interne...
Netflix is considered as a global business invested in strategies of diversification, localisation a...
Recommendation systems are used in hundreds of different services - everywhere from online shopping ...
This paper explores how audiences engage with Netflix as an intermediary in their digital lives, and...
Objectives The main objectives of this study were to explore the factors which influence whether...
Netflix has shaken up audiovisual industry, but what about academic research? This bibliometric anal...