Fake account detection in social media using machine learning methods: literature review

Nalia Graciella Kerrysa, Ika Qutsiati Utami
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Abstract

With the rapid development of emerging technologies in the industrial revolution 4.0 or 5.0, social media has become one of the social environments to carry out social activities, both socializing and advertising. However, since it is an open platform by nature, cybercrime occurrence in social media is inevitable. Currently, more than a million fake accounts are existing on Instagram, Twitter, and Facebook, intending to increase followers, spread hoaxes, and spam. On one hand, it is difficult to manually eliminate these accounts on social media platforms. On the other hand, research on automatic fake account detection has been carried out for more than a decade. This study provides literature reviews aiming to deliver information about several methods and machine learning algorithms with the performances measured in identifying fake accounts on three well-known social media platforms: Twitter, Instagram, and Facebook.
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使用机器学习方法检测社交媒体中的虚假账户:文献综述
随着工业革命 4.0 或 5.0 新兴技术的快速发展,社交媒体已成为开展社交活动(包括社交和广告)的社会环境之一。然而,由于其开放平台的特性,社交媒体上的网络犯罪不可避免。目前,Instagram、Twitter 和 Facebook 上存在超过一百万个虚假账户,其目的是增加粉丝、散布骗局和垃圾邮件。一方面,在社交媒体平台上很难手动清除这些账户。另一方面,关于自动虚假账户检测的研究已经开展了十多年。本研究提供文献综述,旨在提供有关几种方法和机器学习算法的信息,以及在三个知名社交媒体平台上识别虚假账户的性能测定:Twitter、Instagram 和 Facebook。
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来源期刊
Bulletin of Electrical Engineering and Informatics
Bulletin of Electrical Engineering and Informatics Computer Science-Computer Science (miscellaneous)
CiteScore
3.60
自引率
0.00%
发文量
0
期刊介绍: Bulletin of Electrical Engineering and Informatics publishes original papers in the field of electrical, computer and informatics engineering which covers, but not limited to, the following scope: Computer Science, Computer Engineering and Informatics[...] Electronics[...] Electrical and Power Engineering[...] Telecommunication and Information Technology[...]Instrumentation and Control Engineering[...]
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