Analyzing the video popularity characteristics of large-scale user generated content systems

Meeyoung Cha, Haewoon Kwak, Pablo Rodriguez, Yong Yeol Ahn, Sue Moon

Research output: Contribution to journalArticle

299 Citations (Scopus)

Abstract

User generated content (UGC), now with millions of video producers and consumers, is re-shaping the way people watch video and TV. In particular, UGC sites are creating new viewing patterns and social interactions, empowering users to be more creative, and generating new business opportunities. Compared to traditional video-on-demand (VoD) systems, UGC services allow users to request videos from a potentially unlimited selection in an asynchronous fashion. To better understand the impact of UGC services, we have analyzed the world's largest UGC VoD system, YouTube, and a popular similar system in Korea, Daum Videos. In this paper, we first empirically show how UGC services are fundamentally different from traditional VoD services. We then analyze the intrinsic statistical properties of UGC popularity distributions and discuss opportunities to leverage the latent demand for niche videos (or the so-called "the Long Tail" potential), which is not reached today due to information filtering or other system scarcity distortions. Based on traces collected across multiple days, we study the popularity lifetime of UGC videos and the relationship between requests and video age. Finally, we measure the level of content aliasing and illegal content in the system and show the problems aliasing creates in ranking the video popularity accurately. The results presented in this paper are crucial to understanding UGC VoD systems and may have major commercial and technical implications for site administrators and content owners.

Original languageEnglish
Pages (from-to)1357-1370
Number of pages14
JournalIEEE/ACM Transactions on Networking
Volume17
Issue number5
DOIs
Publication statusPublished - 23 Mar 2009
Externally publishedYes

Fingerprint

Video on demand
Information filtering
Industry

Keywords

  • Copyright protection
  • Exponential distributions
  • Human factors
  • Interactive TV
  • Log normal distributions
  • Pareto distributions
  • Probability

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Software
  • Computer Science Applications
  • Computer Networks and Communications

Cite this

Analyzing the video popularity characteristics of large-scale user generated content systems. / Cha, Meeyoung; Kwak, Haewoon; Rodriguez, Pablo; Ahn, Yong Yeol; Moon, Sue.

In: IEEE/ACM Transactions on Networking, Vol. 17, No. 5, 23.03.2009, p. 1357-1370.

Research output: Contribution to journalArticle

Cha, Meeyoung ; Kwak, Haewoon ; Rodriguez, Pablo ; Ahn, Yong Yeol ; Moon, Sue. / Analyzing the video popularity characteristics of large-scale user generated content systems. In: IEEE/ACM Transactions on Networking. 2009 ; Vol. 17, No. 5. pp. 1357-1370.
@article{e947018e54974dc39827334138e8f6f3,
title = "Analyzing the video popularity characteristics of large-scale user generated content systems",
abstract = "User generated content (UGC), now with millions of video producers and consumers, is re-shaping the way people watch video and TV. In particular, UGC sites are creating new viewing patterns and social interactions, empowering users to be more creative, and generating new business opportunities. Compared to traditional video-on-demand (VoD) systems, UGC services allow users to request videos from a potentially unlimited selection in an asynchronous fashion. To better understand the impact of UGC services, we have analyzed the world's largest UGC VoD system, YouTube, and a popular similar system in Korea, Daum Videos. In this paper, we first empirically show how UGC services are fundamentally different from traditional VoD services. We then analyze the intrinsic statistical properties of UGC popularity distributions and discuss opportunities to leverage the latent demand for niche videos (or the so-called {"}the Long Tail{"} potential), which is not reached today due to information filtering or other system scarcity distortions. Based on traces collected across multiple days, we study the popularity lifetime of UGC videos and the relationship between requests and video age. Finally, we measure the level of content aliasing and illegal content in the system and show the problems aliasing creates in ranking the video popularity accurately. The results presented in this paper are crucial to understanding UGC VoD systems and may have major commercial and technical implications for site administrators and content owners.",
keywords = "Copyright protection, Exponential distributions, Human factors, Interactive TV, Log normal distributions, Pareto distributions, Probability",
author = "Meeyoung Cha and Haewoon Kwak and Pablo Rodriguez and Ahn, {Yong Yeol} and Sue Moon",
year = "2009",
month = "3",
day = "23",
doi = "10.1109/TNET.2008.2011358",
language = "English",
volume = "17",
pages = "1357--1370",
journal = "IEEE/ACM Transactions on Networking",
issn = "1063-6692",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "5",

}

TY - JOUR

T1 - Analyzing the video popularity characteristics of large-scale user generated content systems

AU - Cha, Meeyoung

AU - Kwak, Haewoon

AU - Rodriguez, Pablo

AU - Ahn, Yong Yeol

AU - Moon, Sue

PY - 2009/3/23

Y1 - 2009/3/23

N2 - User generated content (UGC), now with millions of video producers and consumers, is re-shaping the way people watch video and TV. In particular, UGC sites are creating new viewing patterns and social interactions, empowering users to be more creative, and generating new business opportunities. Compared to traditional video-on-demand (VoD) systems, UGC services allow users to request videos from a potentially unlimited selection in an asynchronous fashion. To better understand the impact of UGC services, we have analyzed the world's largest UGC VoD system, YouTube, and a popular similar system in Korea, Daum Videos. In this paper, we first empirically show how UGC services are fundamentally different from traditional VoD services. We then analyze the intrinsic statistical properties of UGC popularity distributions and discuss opportunities to leverage the latent demand for niche videos (or the so-called "the Long Tail" potential), which is not reached today due to information filtering or other system scarcity distortions. Based on traces collected across multiple days, we study the popularity lifetime of UGC videos and the relationship between requests and video age. Finally, we measure the level of content aliasing and illegal content in the system and show the problems aliasing creates in ranking the video popularity accurately. The results presented in this paper are crucial to understanding UGC VoD systems and may have major commercial and technical implications for site administrators and content owners.

AB - User generated content (UGC), now with millions of video producers and consumers, is re-shaping the way people watch video and TV. In particular, UGC sites are creating new viewing patterns and social interactions, empowering users to be more creative, and generating new business opportunities. Compared to traditional video-on-demand (VoD) systems, UGC services allow users to request videos from a potentially unlimited selection in an asynchronous fashion. To better understand the impact of UGC services, we have analyzed the world's largest UGC VoD system, YouTube, and a popular similar system in Korea, Daum Videos. In this paper, we first empirically show how UGC services are fundamentally different from traditional VoD services. We then analyze the intrinsic statistical properties of UGC popularity distributions and discuss opportunities to leverage the latent demand for niche videos (or the so-called "the Long Tail" potential), which is not reached today due to information filtering or other system scarcity distortions. Based on traces collected across multiple days, we study the popularity lifetime of UGC videos and the relationship between requests and video age. Finally, we measure the level of content aliasing and illegal content in the system and show the problems aliasing creates in ranking the video popularity accurately. The results presented in this paper are crucial to understanding UGC VoD systems and may have major commercial and technical implications for site administrators and content owners.

KW - Copyright protection

KW - Exponential distributions

KW - Human factors

KW - Interactive TV

KW - Log normal distributions

KW - Pareto distributions

KW - Probability

UR - http://www.scopus.com/inward/record.url?scp=70350561808&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=70350561808&partnerID=8YFLogxK

U2 - 10.1109/TNET.2008.2011358

DO - 10.1109/TNET.2008.2011358

M3 - Article

AN - SCOPUS:70350561808

VL - 17

SP - 1357

EP - 1370

JO - IEEE/ACM Transactions on Networking

JF - IEEE/ACM Transactions on Networking

SN - 1063-6692

IS - 5

ER -