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Detecting Jihadist Messages on Twitter

机译:在Twitter上检测圣战消息

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摘要

Jihadist groups such as ISIS are spreading online propaganda using various forms of social media such as Twitter and YouTube. One of the most common approaches to stop these groups is to suspend accounts that spread propaganda when they are discovered. This approach requires that human analysts manually read and analyze an enormous amount of information on social media. In this work we make a first attempt to automatically detect messages released by jihadist groups on Twitter. We use a machine learning approach that classifies a tweet as containing material that is supporting jihadists groups or not. Even tough our results are preliminary and more tests needs to be carried out we believe that results indicate that an automated approach to aid analysts in their work with detecting radical content on social media is a promising way forward. It should be noted that an automatic approach to detect radical content should only be used as a support tool for human analysts in their work.
机译:ISIS等圣战组织正在使用Twitter和YouTube等各种形式的社交媒体进行在线宣传。阻止这些组的最常见方法之一是暂停发现宣传时传播宣传的帐户。这种方法要求人类分析人员手动阅读和分析社交媒体上的大量信息。在这项工作中,我们首次尝试自动检测圣战组织在Twitter上发布的消息。我们使用机器学习方法将推文归类为包含支持或不支持圣战组织的材料。即使艰难的结果只是初步的,也需要进行更多的测试,我们认为结果表明,一种自动化的方法可以帮助分析人员检测社交媒体中的基本内容,这是一个有希望的前进之路。应该指出的是,检测自由基含量的自动方法仅应用作人类分析人员工作的支持工具。

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