Spam Detection in Social Media Employing Machine Learning Tool for Text Mining

S. Sharmin, Zakia Zaman
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引用次数: 31

Abstract

In recent time, online social networks have been affected by various unwanted threats. Although they provided us with an open platform to share our thoughts with others, however, due to misuse of this powerful resource, general users are in endangered condition. For example, YouTube has been used as a promotional ground by various artist to upload their music videos, movie trailers, etc. and viewers can post their opinion on them. Unfortunately, often malicious users use to post phishing website links, advertisements, and fraudulent information in the comments section, which may transmit viruses or malwares. So, these harmful comments need to be identified in order to continue flawless service of social media. In this study, we have been implemented several classification algorithm to sort out the spam comments on YouTube videos from the legitimate one, their performance measures have been analysed as well as performance of ensemble classifier over single classifier algorithm in the context of text classification has also been highlighted.
利用机器学习工具进行文本挖掘的社交媒体垃圾邮件检测
最近,在线社交网络受到各种不必要的威胁的影响。虽然他们为我们提供了一个开放的平台来与他人分享我们的想法,但是,由于滥用这个强大的资源,普通用户处于危险的境地。例如,YouTube已经被各种艺术家用作宣传平台,上传他们的音乐视频、电影预告片等,观众可以在上面发表自己的意见。不幸的是,恶意用户经常在评论区发布钓鱼网站链接、广告和欺诈信息,这些信息可能会传播病毒或恶意软件。所以,这些有害的评论需要被识别出来,以便继续完美的社交媒体服务。在本研究中,我们实现了几种分类算法来对YouTube视频中的垃圾评论和合法评论进行分类,分析了它们的性能指标,并强调了集成分类器在文本分类背景下优于单一分类器算法的性能。
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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