I tube, you tube, everybody tubes: Analyzing the world’s largest user generated content video system
Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
10-2007
Abstract
User Generated Content (UGC) is re-shaping the way people watch video and TV, with millions of video producers and consumers. In particular, UGC sites are creating new viewing patterns and social interactions, empowering users to be more creative, and developing new business opportunities. To better understand the impact of UGC systems, we have analyzed YouTube, the world's largest UGC VoD system. Based on a large amount of data collected, we provide an in-depth study of YouTube and other similar UGC systems. In particular, we study the popularity life-cycle of videos, the intrinsic statistical properties of requests and their relationship with video age, and the level of content aliasing or of illegal content in the system. We also provide insights on the potential for more efficient UGC VoD systems (e.g. utilizing P2P techniques or making better use of caching). Finally, we discuss the opportunities to leverage the latent demand for niche videos that are not reached today due to information filtering effects or other system scarcity distortions. Overall, we believe that the results presented in this paper are crucial in understanding UGC systems and can provide valuable information to ISPs, site administrators, and content owners with major commercial and technical implications.
Keywords
user generated content, power-law, long tail, VoD, P2P, caching, popularity analysis, content aliasing
Discipline
Databases and Information Systems
Research Areas
Data Science and Engineering; Intelligent Systems and Optimization
Publication
Proceedings of the ACM SIGCOMM Internet Measurement Conference, IMC 2007, San Diego, CA, United States, October 24-26
First Page
1
Last Page
14
ISBN
9781595939081
Identifier
10.1145/1298306.1298309
Publisher
ACM
City or Country
New York
Citation
1
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://dl.acm.org/doi/10.1145/1298306.1298309