SPAMMER DETECTION AND FAKE USER RECOGNITION IN OSN

Abstract

Social networking sites engage millions of users around the world. The user’s
interactions with these social sites, such as Twitter and Facebook have a tremendous impact
and occasionally undesirable repercussions for daily life. The prominent social networking
sites have turned into a target platform for the spammers to disperse a huge amount of
irrelevant and deleterious information. Twitter, for example, has become one of the most
extravagantly used platforms of all times and therefore allows an unreasonable amount of
spam. Fake users send undesired tweets to users to promote services or websites that not only
affect legitimate users but also disrupt resource consumption. Moreover, the possibility of
expanding invalid information to users through fake identities has increased that results in
the unrolling of harmful content. Recently, the detection of spammers and identification of
fake users on Twitter has become a common area of research in contemporary online social
Networks (OSNs). In this paper, we perform a review of techniques used for detecting
spammers on Twitter.