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Open AccessProceedings ArticleDOI

I tube, you tube, everybody tubes: analyzing the world's largest user generated content video system

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TLDR
In this article, the authors analyzed YouTube, the world's largest UGC VoD system, and provided an in-depth study of the popularity life cycle of videos, intrinsic statistical properties of requests and their relationship with video age, and the level of content aliasing or of illegal content.
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.

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Citations
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Journal ArticleDOI

A distributed, architecture-centric approach to computing accurate recommendations from very large and sparse datasets

TL;DR: This work introduces a novel architecture model that supports scalable, distributed suggestions from multiple independent nodes, and proposes a novel algorithm that generates a more optimal recommender input, which is the reason for a considerable accuracy improvement.
Journal ArticleDOI

Predicting the popularity of online content

TL;DR: In this article, a method for predicting the long-term popularity of online content from early measurements of user access is presented, using two content sharing portals, Youtube and Digg, using the accrual of views and votes on content offered by these services.
Posted Content

Predicting the popularity of online content

TL;DR: Early patterns of Digg diggs and YouTube views reflect long-term user interest, according to research published in the journal “Attention to Detail .”
Journal ArticleDOI

How Does Brand-related User-generated Content Differ across YouTube, Facebook, and Twitter?

TL;DR: In this article, the authors test hypotheses regarding differences in brand-related user-generated content (UGC) between Twitter (a microblogging site), Facebook (a social network) and YouTube (a content community) using data from a content analysis of 600 UGC posts for two retail-apparel brands.
Proceedings ArticleDOI

Statistics and Social Network of YouTube Videos

TL;DR: The social networking in YouTube videos is investigated, finding that the links to related videos generated by uploaders' choices have clear small-world characteristics, indicating that the videos have strong correlations with each other, and creates opportunities for developing novel techniques to enhance the service quality.
References
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Journal ArticleDOI

Emergence of Scaling in Random Networks

TL;DR: A model based on these two ingredients reproduces the observed stationary scale-free distributions, which indicates that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.
Journal ArticleDOI

Power laws, Pareto distributions and Zipf's law

Mark Newman
- 01 Sep 2005 - 
TL;DR: Some of the empirical evidence for the existence of power-law forms and the theories proposed to explain them are reviewed.
Journal ArticleDOI

Classes of small-world networks

TL;DR: Evidence of the occurrence of three classes of small-world networks, characterized by a vertex connectivity distribution that decays as a power law law, and the nature of such constraints may be the controlling factor for the emergence of different classes of networks are presented.
Journal ArticleDOI

Self-similarity in World Wide Web traffic: evidence and possible causes

TL;DR: It is shown that the self-similarity in WWW traffic can be explained based on the underlying distributions of WWW document sizes, the effects of caching and user preference in file transfer, the effect of user "think time", and the superimposition of many such transfers in a local-area network.
Journal ArticleDOI

Log-normal Distributions across the Sciences: Keys and Clues

TL;DR: Many widely used statistical methods, such as ANOVA (analysis of variance) and regression analysis, require that the data be normally distributed, but only rarely is the frequency distribution of data tested when these techniques are used.
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