Exploring the User-Generated Content (UGC) Uploading Behavior on YouTube

被引:5
作者
Park, Jaimie Y. [1 ]
Jang, Jiyeon [2 ]
Jaimes, Alejandro [3 ]
Chung, Chin-Wan [4 ]
Myaeng, Sung-Hyon [4 ]
机构
[1] Korea Adv Inst Sci & Technol, Div Web Sci & Technol, Daejeon, South Korea
[2] Korea Adv Inst Sci & Technol, Dept Comp Sci, Daejeon, South Korea
[3] Yahoo Labs, New York, NY USA
[4] Korea Adv Inst Sci & Technol, Div Web Sci & Tech, Dept Comp Sci, Daejeon, South Korea
来源
WWW'14 COMPANION: PROCEEDINGS OF THE 23RD INTERNATIONAL CONFERENCE ON WORLD WIDE WEB | 2014年
基金
新加坡国家研究基金会;
关键词
Human Factors; Measurement; User Generated Content; YouTube; Popularity Analysis; Digital Media; Social Media; Video Streaming Service; POPULARITY;
D O I
10.1145/2567948.2576945
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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 nonprofessionals, which we refer to as user-generated content (UGCs). Non-professional users frequently upload content (UGCs) 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 UGCs 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 UGCs. 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 UGCs are 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 UGCs is important in order to understand and to predict the popularity of the original content.
引用
收藏
页码:529 / 534
页数:6
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