仇恨、淫秽和侮辱：测量儿童对YouTube中不适当评论的暴露
Hate, Obscenity, and Insults: Measuring the Exposure of Children to Inappropriate Comments in YouTube
摘要：
社交媒体已成为儿童和青少年日常生活的重要组成部分。此外，还做出了巨大努力，以确保年轻用户的心理和情感健康以及他们在与各种社交媒体平台互动时的安全。在本文中，我们调查了这些用户在YouTube视频上发布的针对这一人群的不当评论的曝光情况。我们收集了大约400万条记录的大规模数据集，并研究了五个年龄不合适的类别的存在以及每个类别的暴露量。使用自然语言处理和机器学习技术，我们构建了集成分类器，在检测不适当的评论，实现了高准确率。我们的研究结果显示，很大一部分令人担忧的评论含有不适当的内容：我们发现11%的儿童视频评论是有毒的，这凸显了监控评论的重要性，特别是在儿童平台上。
英文摘要：
Social media has become an essential part of the daily routines of children and adolescents. Moreover, enormous efforts have been made to ensure the psychological and emotional well-being of young users as well as their safety when interacting with various social media platforms. In this paper, we investigate the exposure of those users to inappropriate comments posted on YouTube videos targeting this demographic. We collected a large-scale dataset of approximately four million records and studied the presence of five age-inappropriate categories and the amount of exposure to each category. Using natural language processing and machine learning techniques, we constructed ensemble classifiers that achieved high accuracy in detecting inappropriate comments. Our results show a large percentage of worrisome comments with inappropriate content: we found 11% of the comments on children's videos to be toxic, highlighting the importance of monitoring comments, particularly on children's platforms.
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。
