TubeSpam: Comment Spam Filtering on YouTube
TubeSpam: Comment Spam Filtering on YouTube
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TubeSpam：YouTube 上的垃圾评论过滤
DOI：
10.1109/icmla.2015.37
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
Tiago A. Almeida
中科院分区：
文献类型：
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作者：
Túlio C. Alberto;Johannes V. Lochter;Tiago A. Almeida
谷歌在其全新的视频分发平台YouTube上宣传的盈利能力吸引了越来越多的用户。然而，这样的成功也吸引了恶意用户，他们的目的是自我推销他们的视频或传播病毒和恶意软件。由于YouTube提供有限的评论审核工具，垃圾邮件数量惊人地增加，导致著名频道的所有者在他们的视频中禁用评论部分。YouTube上的自动垃圾评论过滤即使对于已建立的分类方法也是一个挑战，因为这些消息非常短，并且经常充斥着俚语，符号和缩写。在这项工作中，我们已经评估了几个最高性能的分类技术，用于这样的目的。统计分析结果表明，在99.9%的置信水平下，决策树、逻辑回归、Bernoulli朴素贝叶斯、随机森林、线性和高斯支持向量机在统计上是等价的。在此基础上，我们还提供了TubeSpam -一个准确的在线系统来过滤YouTube上发布的评论。
The profitability promoted by Google in its brand new video distribution platform YouTube has attracted an increasing number of users. However, such success has also attracted malicious users, which aim to self-promote their videos or disseminate viruses and malwares. Since YouTube offers limited tools for comment moderation, the spam volume is shockingly increasing which lead owners of famous channels to disable the comments section in their videos. Automatic comment spam filtering on YouTube is a challenge even for established classification methods, since the messages are very short and often rife with slangs, symbols and abbreviations. In this work, we have evaluated several top-performance classification techniques for such purpose. The statistical analysis of results indicate that, with 99.9% of confidence level, decision trees, logistic regression, Bernoulli Naive Bayes, random forests, linear and Gaussian SVMs are statistically equivalent. Based on this, we have also offered the TubeSpam - an accurate online system to filter comments posted on YouTube.