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Exploring the user-generated content (UGC) uploading behavior on youtube

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Sung-Hyon MyaengAuthors Info & Claims

WWW '14 Companion: Proceedings of the 23rd International Conference on World Wide Web

Pages 529 - 534

https://doi.org/10.1145/2567948.2576945

Published: 07 April 2014 Publication History

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Abstract

YouTube is the world's largest video sharing platform where both professional and non-professional users participate in creating, uploading, and viewing content. In this work, we analyze content in the music category created by the non-professionals, which we refer to as user-generated content (UGC). Non-professional users frequently upload content (UGC) that are parodies, remakes, or covers of the music videos uploaded by professionals, namely the official record labels. Along with the success of official music videos on YouTube, we find the increased participation of users in creating the UGC related to the music videos. In this study, we characterize the UGC uploading behavior in terms of what, where, and when. Furthermore, we measure the relationship between the popularity of the original content and creation of the related UGC. We find that the UGC uploading behavior is different depending on the types of the UGC and across different genres of music videos. We also find that UGC sharing is a highly global activity; popular UGC is created from all over the world despite the fact that the popular music videos originate from a very limited number of locations. Our findings imply that utilizing the information on re-created UGC is important in order to understand and to predict the popularity of the original content.

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Cited By

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Corvite SHui J(2024)Social Media as a Lens into Careers During a Changing World of WorkProceedings of the ACM on Human-Computer Interaction10.1145/36870538:CSCW2(1-27)Online publication date: 8-Nov-2024
https://dl.acm.org/doi/10.1145/3687053
Song LWu WFu CLoy CHe R(2023)Audio-Driven Dubbing for User Generated Contents via Style-Aware Semi-Parametric SynthesisIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2022.321000233:3(1247-1261)Online publication date: Mar-2023
https://doi.org/10.1109/TCSVT.2022.3210002
Choi SChoi SLee J(2020)An Analysis of M/V Fandom on YouTube : BTS M/V View, Comment Interaction, and Meme ProductionKorean Journal of Journalism & Communication Studies10.20879/kjjcs.2020.64.1.00164:1(7-45)Online publication date: 29-Feb-2020
https://doi.org/10.20879/kjjcs.2020.64.1.001
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Index Terms

Exploring the user-generated content (UGC) uploading behavior on youtube
1. Information systems
  1. World Wide Web
    1. Web applications
    2. Web services

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Published In

WWW '14 Companion: Proceedings of the 23rd International Conference on World Wide Web

April 2014

1396 pages

ISBN:9781450327459

DOI:10.1145/2567948

General Chair:
Chin-Wan Chung
Korea Advanced Institute of Science and Technology, Korea
,
Program Chairs:
Andrei Broder
Google Inc., USA
,
Kyuseok Shim
Seoul National University, Korea
,
Torsten Suel
New York University, USA

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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

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Association for Computing Machinery

New York, NY, United States

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Published: 07 April 2014

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National Research Foundation of Korea

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WWW '14

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IW3C2

WWW '14: 23rd International World Wide Web Conference

April 7 - 11, 2014

Seoul, Korea

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Corvite SHui J(2024)Social Media as a Lens into Careers During a Changing World of WorkProceedings of the ACM on Human-Computer Interaction10.1145/36870538:CSCW2(1-27)Online publication date: 8-Nov-2024
https://dl.acm.org/doi/10.1145/3687053
Song LWu WFu CLoy CHe R(2023)Audio-Driven Dubbing for User Generated Contents via Style-Aware Semi-Parametric SynthesisIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2022.321000233:3(1247-1261)Online publication date: Mar-2023
https://doi.org/10.1109/TCSVT.2022.3210002
Choi SChoi SLee J(2020)An Analysis of M/V Fandom on YouTube : BTS M/V View, Comment Interaction, and Meme ProductionKorean Journal of Journalism & Communication Studies10.20879/kjjcs.2020.64.1.00164:1(7-45)Online publication date: 29-Feb-2020
https://doi.org/10.20879/kjjcs.2020.64.1.001
Mariconti ESuarez-Tangil GBlackburn JDe Cristofaro EKourtellis NLeontiadis ISerrano JStringhini G(2019)"You Know What to Do"Proceedings of the ACM on Human-Computer Interaction10.1145/33593093:CSCW(1-21)Online publication date: 7-Nov-2019
https://dl.acm.org/doi/10.1145/3359309
Xu WPark JKim JPark H(2016)Networked Cultural Diffusion and Creation on YouTube: An Analysis of YouTube MemesJournal of Broadcasting & Electronic Media10.1080/08838151.2015.112724160:1(104-122)Online publication date: Mar-2016
https://doi.org/10.1080/08838151.2015.1127241

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

Workload generation for YouTube

Design for creating, uploading and sharing user generated content

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