计算机科学
用户参与度
视频质量
用户生成的内容
背景(考古学)
体验质量
多媒体
质量(理念)
互联网视频
PEVQ公司
视频点播
互联网
渲染(计算机图形)
用户体验设计
服务质量
视频处理
万维网
计算机网络
人机交互
视频跟踪
社会化媒体
多视点视频编码
计算机图形学(图像)
哲学
公制(单位)
经济
人工智能
古生物学
认识论
生物
运营管理
作者
Florin Dobrian,Vyas Sekar,Asad Awan,Ion Stoica,Dilip Joseph,Aditya Ganjam,Jibin Zhan,Hui Zhang
出处
期刊:Computer Communication Review
[Association for Computing Machinery]
日期:2011-08-15
卷期号:41 (4): 362-373
被引量:293
标识
DOI:10.1145/2043164.2018478
摘要
As the distribution of the video over the Internet becomes main- stream and its consumption moves from the computer to the TV screen, user expectation for high quality is constantly increasing. In this context, it is crucial for content providers to understand if and how video quality affects user engagement and how to best invest their resources to optimize video quality. This paper is a first step towards addressing these questions. We use a unique dataset that spans different content types, including short video on demand (VoD), long VoD, and live content from popular video con- tent providers. Using client-side instrumentation, we measure quality metrics such as the join time, buffering ratio, average bitrate, rendering quality, and rate of buffering events. We quantify user engagement both at a per-video (or view) level and a per-user (or viewer) level. In particular, we find that the percentage of time spent in buffering (buffering ratio) has the largest impact on the user engagement across all types of content. However, the magnitude of this impact depends on the content type, with live content being the most impacted. For example, a 1% increase in buffering ratio can reduce user engagement by more than three minutes for a 90-minute live video event. We also see that the average bitrate plays a significantly more important role in the case of live content than VoD content.
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