Dialing for Videos: A Random Sample of YouTube

Ryan McGrady, Kevin Zheng, Rebecca Curran, Jason Baumgartner, Ethan Zuckerman
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Abstract

YouTube is one of the largest, most important communication platforms in the world, but while there is a great deal of research about the site, many of its fundamental characteristics remain unknown. To better understand YouTube as a whole, we created a random sample of videos using a new method. Through a description of the sample’s metadata, we provide answers to many essential questions about, for example, the distribution of views, comments, likes, subscribers, and categories. Our method also allows us to estimate the total number of publicly visible videos on YouTube and its growth over time. To learn more about video content, we hand-coded a subsample to answer questions like how many are primarily music, video games, or still images. Finally, we processed the videos’ audio using language detection software to determine the distribution of spoken languages. In providing basic information about YouTube as a whole, we not only learn more about an influential platform, but also provide baseline context against which samples in more focused studies can be compared.
拨号观看视频YouTube 随机样本
YouTube 是世界上最大、最重要的交流平台之一,但尽管对该网站进行了大量研究,其许多基本特征仍不为人所知。为了更好地了解 YouTube 的整体情况,我们采用了一种新方法,创建了一个视频随机样本。通过对样本元数据的描述,我们回答了许多基本问题,例如浏览量、评论、点赞、订阅者和类别的分布。我们的方法还允许我们估算 YouTube 上公开可见视频的总数及其随时间推移的增长情况。为了进一步了解视频内容,我们对子样本进行了手工编码,以回答有多少视频主要是音乐、视频游戏或静态图片等问题。最后,我们使用语言检测软件处理了视频音频,以确定口语的分布情况。通过提供有关 YouTube 整体的基本信息,我们不仅进一步了解了这个极具影响力的平台,而且还提供了基线背景,以便将更多重点研究中的样本进行比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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