A Real-world Dataset of Netflix Videos and User Watch-Behavior: Analysis and Insights

Netflix is the most popular video streaming site contributing to nearly a quarter of global video traffic. Given the dominance of Netflix on Internet traffic, understanding how individual users consume content on Netflix is of interest to not only the research community, but to network operators, co...

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Bibliographic Details
Main Authors: Lall, Shruti, Sivakumar, Raghupathy
Format: Conference Proceeding
Language:English
Subjects:
Conferences
Internet
Motion pictures
Predictive models
Streaming media
Online Access:Request full text
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Summary:Netflix is the most popular video streaming site contributing to nearly a quarter of global video traffic. Given the dominance of Netflix on Internet traffic, understanding how individual users consume content on Netflix is of interest to not only the research community, but to network operators, content creators and providers, users and advertisers. In this context, we collect Netflix viewing activity from 1060 users spanning a 1 year period, and consisting of over 1.7 million episodes and movies. We group the users based on their activity level, and provide key insights pertaining to the user's watch patterns, watch-session length, user preferences, predictability and watch-behavior continuation tendencies. We also implement and evaluate classifiers which are used to predict the user's engagement in a series based on their past behavioral patterns.
ISSN:1938-1883
DOI:10.1109/ICC42927.2021.9500669