Keyword

Netflix

Description: An American subscription-based streaming service that distributes films, television programs, and other video content over the internet.

Primary topic: Legal Systems and Institutions (26%)

Wikidata ID: wiki/Q907311

OpenAlex ID: keywords/netflix

The Netflix Recommender System

2015 · Carlos A. Gomez-Uribe, Neil Hunt · ACM Transactions on Management Information Systems · 1,414

Exposure and Use of Mobile Media Devices by Young Children

2015 · Hilda K. Kabali, Matilde M. Irigoyen, et al. · PEDIATRICS · 1,051

A buffer-based approach to rate adaptation

2014 · Te-Yuan Huang, Ramesh Johari, et al. · 1,007

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Innovation and Design in the Age of Artificial Intelligence

2020 · Roberto Verganti, Luca Vendraminelli, et al. · Journal of Product Innovation Management · 845

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An experimental evaluation of rate-adaptation algorithms in adaptive streaming over HTTP

2011 · Saamer Akhshabi, Ali C. Begen, et al. · 608

Netflix Nations

2019 · Ramon Lobato · New York University Press eBooks · 523

Creating new markets through service innovation

2006 · Leonard L. Berry, Janet Turner Parish, et al. · Dialnet (Universidad de la Rioja) · 464

Crafting and Executing Strategy : The Quest for Competitive Advantage - Concepts and Cases

2004 · Arthur A. Thompson · 421

Unreeling netflix: Understanding and improving multi-CDN movie delivery

2012 · Vijay Kumar Adhikari, Yang Guo, et al. · IEEE Conference on Computer Communications (INFOCOM) · 375

Netflix and the Re-invention of Television

2018 · Mareike Jenner · Springer eBooks · 366

Confused, timid, and unstable

2012 · Te-Yuan Huang, Nikhil Handigol, et al. · Internet Measurement Conference · 336

Globalization of the Business

2017 · Joseph N. Cohen · Routledge eBooks · 328

Is this TVIV? On Netflix, TVIII and binge-watching

2014 · Mareike Jenner · New Media & Society · 321

A new collaborative filtering metric that improves the behavior of recommender systems

2010 · J. Bobadilla, F. Serradilla, et al. · Knowledge-Based Systems · 315

A buffer-based approach to rate adaptation

2014 · Te-Yuan Huang, Ramesh Johari, et al. · ACM SIGCOMM Computer Communication Review · 308

Network characteristics of video streaming traffic

2011 · Ashwin Rao, Arnaud Legout, et al. · 303

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Chaos Engineering

2016 · Ali Basiri, Niosha Behnam, et al. · IEEE Software · 296

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The Netflix Effect Technology and Entertainment in the 21st Century

2016 · 248

An Introduction to Recommender Systems

2016 · Charu C. Aggarwal · Springer eBooks · 241

The Netflix Effect: Teens, Binge Watching, and On-Demand Digital Media Trends

2014 · Sidneyeve Matrix · Jeunesse Young People Texts Cultures · 240

Matchbox

2009 · David H. Stern, Ralf Herbrich, et al. · International World Wide Web Conference (WWW) · 221

Alternating least squares for personalized ranking

2012 · Gábor Takács, Domonkos Tikk · ACM Conference on Recommender Systems (RecSys) · 218

Irresistible: The Rise of Addictive Technology and the Business of Keeping Us Hooked

2017 · Adam L. Alter · 209

Sprinting a media marathon: Uses and gratifications of binge-watching television through Netflix

2015 · Matthew Pittman, Kim Sheehan · First Monday · 208

Association Between the Release of Netflix’s 13 Reasons Why and Suicide Rates in the United States: An Interrupted Time Series Analysis

2019 · Jeffrey A. Bridge, Joel B. Greenhouse, et al. · Journal of the American Academy of Child & Adolescent Psychiatry · 194

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Works count: 11,590

Citation count: 37,390