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Bot or not

机译:僵尸与否

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In recent years, Twitter, a social networking website, has been affected by a steady rise in spam on its network. Hijacking of social media accounts has become a modern-day danger. Motivations for this can range from attempts in identity theft to simply skewing the perception of an audience. In this paper, we extend our previous work, Engineering Your Social Network to Detect Fraudulent Profiles, by doing an investigation of spam bots on Twitter. We propose an algorithm that will distinguish a spam bot, from a genuine user account by using a JavaScript testing framework that consumes Twitter's REST API. We ran a dataset of 700 Twitter accounts through our algorithm and identified that roughly 11% of the dataset were bots.
机译:近年来,社交网站Twitter受其网络上垃圾邮件数量稳定增长的影响。劫持社交媒体帐户已成为当今的危险。动机可能从身份盗用尝试到仅仅歪曲观众的感知范围不等。在本文中,我们通过对Twitter上的垃圾邮件机器人进行调查,扩展了我们以前的工作,“设计您的社交网络以检测欺诈性配置文件”。我们提出了一种算法,该算法通过使用消耗Twitter REST API的JavaScript测试框架,将垃圾邮件机器人与真正的用户帐户区分开。我们通过算法运行了700个Twitter帐户的数据集,并确定大约11%的数据集是机器人。

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