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Abstract

The issue of spam in various Social Networking Sites has become very trivial these days. There are various users in the outside world who have turned into spammers in order to earn their benefits. So, to deal with the problem of spam, there arises techniques for Spam Classification through which a user can take preventive measures beforehand. This paper gives insight about various spam classification techniques like Naïve Bayes, Support Vector Machine, URL analysis etc. Also, this paper focuses on spam classification techniques used mainly for Twitter as Twitter is considered one of the vulnerable and sensitive Social Networking platform.

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Keywords

Spam , Spam Classification , Naïve Bayes , Support Vector Machine , URL analysis.