Insight Data of YouTube from a Partner's View

Authors:
Xu Cheng;Mehrdad Fatourechi;Xiaoqiang Ma;Cong Zhang;Lei Zhang;Jiangchuan Liu
Affiliations:
BroadbandTV Corp., British Columbia, Canada and School of Computing Science, Simon Fraser University, British Columbia, Canada;BroadbandTV Corp., British Columbia, Canada;School of Computing Science, Simon Fraser University, British Columbia, Canada;School of Computing Science, Simon Fraser University, British Columbia, Canada;School of Computing Science, Simon Fraser University, British Columbia, Canada;School of Computing Science, Simon Fraser University, British Columbia, Canada
Venue:
Proceedings of Network and Operating System Support on Digital Audio and Video Workshop
Year:
2014

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Abstract

YouTube is arguably the most popular online videos sharing site nowadays. To further augment its service with better revenue, it has started working with content owners (known as YouTube partners) whose copyrighted videos and channels have pulled massive audience. By uploading high-quality premium videos, the partners have essentially changed the user-generated content feature of YouTube and further increased YouTube's popularity. Understanding the latest YouTube access pattern is thus crucial to both YouTube and its partners, as well as to other providers of relevant services. In this paper, we for the first time analyze a large-scale YouTube dataset from a partner's view. We make effective use of Insight, a new analytics service of YouTube that offers inside statistics for partners about their content accesses and audience behaviours. From the raw Insight data that are confined to simple scalars and charts, we reveal the inherent relationship among the various metrics that affect the popularity of the videos. Our findings facilitate YouTube partners to adapt their content deployment and user engagement strategies, having great potentials for them to collaborate with YouTube to generate more views and subsequently increasing their revenues.