Title: Detecting spams in social networks using ML algorithms - a review

Authors: N. Senthil Murugan; G. Usha Devi

Addresses: School of Information Technology and Engineering, VIT University, Vellore, Tamil Nadu, India ' School of Information Technology and Engineering, VIT University, Vellore, Tamil Nadu, India

Abstract: The social network, by the name which has popularised in today's world and growing rapidly at all times and controlling over mankind. The social networks like Twitter, Facebook, and LinkedIn, etc., have become a regular and daily usage of many people. It becomes a good mediator for the people who would like to share some posts, are some of their own videos, or some messages. But there has been major issues that the particular user of the social networks like Twitter and Facebook have the problem of indiscipline actions which we call as spam, by the third person who is knowingly doing this to spoil their intention and good opinion upon each other. Also, these spams help to steal information about the people who using social networks. In this paper, we study and analyse about the spam in social networks and machine learning algorithms to detect such kind of spams. This paper also focuses on the ML algorithms detection rate and false positive rate over different datasets.

Keywords: social network; spam; machine learning; Twitter; Facebook; detection rate.

DOI: 10.1504/IJEWM.2018.091308

International Journal of Environment and Waste Management, 2018 Vol.21 No.1, pp.22 - 36

Received: 28 Jan 2017
Accepted: 21 Apr 2017
Published online: 24 Apr 2018 *

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