14Spammer Detection in Online Social Networks
Rahin Batcha R.1*, D. Saravanan1, Vijay Ramalingam1, T. Ragupathi1, Arul Prakash A.1, S. Vignesh1, Belsam Jeba Ananth M.2 and K. Arumugam3
1Department of Computer Science and Engineering, Sathyabama Institute of Science and Technology, Chennai, India
2Mechatronics Engineering, SRM Institute of Science and Technology, Kattankulathur, Chengalpattu, Tamil Nadu, India
3Department of Computer Applications, Bharathiar University, Coimbatore, Tamil Nadu, India
Abstract
Online social networks (OSNs) are becoming so ingrained in people’s daily lives that they make it easier for individuals to share and express opinions on any subject. Furthermore, the communication is carried out in a way that is both economical and efficient. “Online social spammers” are malicious user accounts that take use of the OSN’s features to send unsolicited messages. Spammers present their content in a way that is attractive to real network users in order to get a reaction from them. Spammers use a variety of strategies, each suited to a particular situation, to promote their own financial goals. OSNs have been shown to provide fertile ground for novel types of cybercrime, such as cyberbullying, disinformation propagation, stalking, identity fraud, radicalization, and other unlawful activities, in addition to more established ones like spam, phishing, and drive-by downloads. This chapter consists of a framework for spammer detection using machine learning. Social ...
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