Twitter fake account detection

Buket Erşahin, Özlem Aktaş, Deniz Kılınç, Ceyhun Akyol
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引用次数: 79

Abstract

Social networking sites such as Twitter and Facebook attracts millions of users across the world and their interaction with social networking has affected their life. This popularity in social networking has led to different problems including the possibility of exposing incorrect information to their users through fake accounts which results to the spread of malicious content. This situation can result to a huge damage in the real world to the society. In our study, we present a classification method for detecting the fake accounts on Twitter. We have preprocessed our dataset using a supervised discretization technique named Entropy Minimization Discretization (EMD) on numerical features and analyzed the results of the Naïve Bayes algorithm.
推特虚假账户检测
Twitter和Facebook等社交网站吸引了全球数百万用户,他们与社交网络的互动影响了他们的生活。社交网络的流行带来了不同的问题,包括通过虚假账户向用户暴露错误信息的可能性,从而导致恶意内容的传播。这种情况会在现实世界中对社会造成巨大的损害。在我们的研究中,我们提出了一种分类方法来检测Twitter上的虚假账户。我们使用一种名为熵最小化离散化(EMD)的监督离散化技术对数据集进行了预处理,并分析了Naïve贝叶斯算法的结果。
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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