儿童受干扰的YouTube：表征和检测针对幼儿的不适当视频
Disturbed YouTube for Kids: Characterizing and Detecting Inappropriate Videos Targeting Young Children
摘要：
订阅量最大的YouTube频道中有大量是针对年龄很小的儿童的。YouTube上有数百个面向幼儿的频道，提供无害、制作精良和教育性的视频。不幸的是，针对这一人群的不适当内容也很常见。令人遗憾的是，YouTube的算法推荐系统会推荐不合适的内容，因为其中一些内容模仿或衍生自其他合适的内容。考虑到幼儿发展的风险，以及幼儿消费YouTube媒体的增长趋势，这是一个令人担忧的问题。在这项工作中，我们建立了一个分类器，能够以84.3%的准确率识别YouTube上针对幼儿的不适当内容，并利用它来执行首次大规模定量表征，揭示了幼儿YouTube媒体消费的一些风险。我们的分析表明，YouTube仍然受到这些令人不安的视频的困扰，其目前部署的反措施在及时检测它们方面是无效的。令人担忧的是，使用我们的分类器，我们发现幼儿不仅能够，而且可能会在从良性视频开始随机浏览平台时遇到令人不安的视频。
英文摘要：
A large number of the most-subscribed YouTube channels target children of a very young age. Hundreds of toddler-oriented channels on YouTube feature inoffensive, well-produced, and educational videos. Unfortunately, inappropriate content that targets this demographic is also common. YouTube's algorithmic recommendation system regrettably suggests inappropriate content because some of it mimics or is derived from otherwise appropriate content. Considering the risk for early childhood development, and an increasing trend in toddler's consumption of YouTube media, this is a worrisome problem. In this work, we build a classifier able to discern inappropriate content that targets toddlers on YouTube with 84.3% accuracy, and leverage it to perform a first-of-its-kind, large-scale, quantitative characterization that reveals some of the risks of YouTube media consumption by young children. Our analysis reveals that YouTube is still plagued by such disturbing videos and its currently deployed counter-measures are ineffective in terms of detecting them in a timely manner. Alarmingly, using our classifier we show that young children are not only able, but likely to encounter disturbing videos when they randomly browse the platform starting from benign videos.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
