Cyber Times International Journal of Technology & Management

Facebook is a global name, none of us today are unrecognized by it. It has around 1.44 billion active users, due to its highly acclaimed Popularity worldwide Facebook has allured significantly high number of spammers, fake accounts and fake groups attacking user’s privacy and rights. A lot of groups nowadays on Facebook are high on increasing Spamming activities, which greatly affects the quality of a group leading to more spams than real posts. A group originally started for some work/ activity eventually turns into no less than a spam group. In this paper using the Facebook API methods, various group activities were crawled, user activities, user’s likes and comments, number of spam links. Thereby collecting dataset for classifying results. The results showed 90.7% precision in Bayesian and 93.4% precision in K-NN classification algorithms.