Analyzing the video popularity characteristics of large-scale user generated content systems
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. Comp...
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sg-smu-ink.sis_research-63272020-10-23T07:45:56Z Analyzing the video popularity characteristics of large-scale user generated content systems CHA, Meeyoung KWAK, Haewoon RODRIGUEZ, Pablo AHN, Yong-Yeol MOON, Sue 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. 2009-10-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/5323 info:doi/10.1109/TNET.2008.2011358 https://ink.library.smu.edu.sg/context/sis_research/article/6327/viewcontent/analyzing_video___PV.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Interactive TV human factors exponential distributions log normal distributions pareto distributions probability copyright protection Databases and Information Systems Hardware Systems |
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Interactive TV human factors exponential distributions log normal distributions pareto distributions probability copyright protection Databases and Information Systems Hardware Systems CHA, Meeyoung KWAK, Haewoon RODRIGUEZ, Pablo AHN, Yong-Yeol MOON, Sue Analyzing the video popularity characteristics of large-scale user generated content systems |
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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. |
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CHA, Meeyoung KWAK, Haewoon RODRIGUEZ, Pablo AHN, Yong-Yeol MOON, Sue |
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CHA, Meeyoung KWAK, Haewoon RODRIGUEZ, Pablo AHN, Yong-Yeol MOON, Sue |
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CHA, Meeyoung |
title |
Analyzing the video popularity characteristics of large-scale user generated content systems |
title_short |
Analyzing the video popularity characteristics of large-scale user generated content systems |
title_full |
Analyzing the video popularity characteristics of large-scale user generated content systems |
title_fullStr |
Analyzing the video popularity characteristics of large-scale user generated content systems |
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Analyzing the video popularity characteristics of large-scale user generated content systems |
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analyzing the video popularity characteristics of large-scale user generated content systems |
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Institutional Knowledge at Singapore Management University |
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2009 |
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https://ink.library.smu.edu.sg/sis_research/5323 https://ink.library.smu.edu.sg/context/sis_research/article/6327/viewcontent/analyzing_video___PV.pdf |
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