A Survey on Spam Detection in Twitter

Abstract

Social Networking sites have become popular in recent years, among these sites Twitter is one of the fastest growing site. It plays a dual role of Online Social Networking (OSN) and Micro Blogging. Spammers invade twitter trending topics (popular topics discussed by Twitter user) to pollute the useful content. Social spamming is more successful compared to email spamming by using social relationship between the users. Spam detection is important because Twitter is mainly used for commercial advertisement and spammers invade the privacy information of the user and also the reputation of the user is damaged. Spammers can be detected using content and user based attributes. Traditional classifiers are required for spam detection. The contribution of this work is bifold, first to detect spam content in Twitter and preventing it being displayed. Second is to design a new classifier to detect spammers with accuracy.