Three-year Trends in YouTube Video Content and Encoding
Feng Li, Jae Won Chung, and Mark Claypool
Despite the dominance of YouTube streaming traffic, there have been few studies focusing on characterizing YouTube videos over time. Given the sheer volume of YouTube videos, we created a custom crawler which took snapshots of popular YouTube channels and ran the crawler daily for the past 3 years. This provides YouTube video trends from 2018-2020 for over 160k videos, considering media type, duration, bit rate, resolution, codec, encoding format, and popularity. Analysis of the data shows YouTube videos have increased frame rates, resolutions and durations over this time, with the biggest clips consuming over 200 Mb/s and being over 3 hours long, accompanied by corresponding changes in encoding rates and codecs. Our analysis and the resulting dataset we make public should be beneficial for traffic shaping or CDN deployment strategies.
Feng Li, Jae Chung and Mark Claypool. Silhouette - Identifying YouTube Video Flows from Encrypted Traffic, In Proceedings of the 28th ACM International Workshop on Network and Operating Systems Support for Digital Audio and Video (NOSSDAV), Amsterdam, The Netherlands, June 2018. Online at: http://www.cs.wpi.edu/~claypool/papers/yt-crawler/