• J.Veenasa
• Dr. R. Jegadeesan
• P.Pravalika
• B.Aravind
• P.Prasad

Twitter is one in all the foremost in style microblogging services, that is mostly wont to share news and updates through short messages restricted to 280 characters. However, its open nature and enormous user base are often exploited by machine-controlled spammers, content polluters, and alternative ill-intended users to commit numerous cyber crimes, like cyberbullying, trolling, rumor dissemination, and stalking. consequently, variety of approaches are projected by researchers to handle these issues. However, most of those approaches are supported user characterization and fully regardless mutual interactions. during this study, we tend to gift a hybrid approach for police work machine-controlled spammers by amalgamating community primarily based options with alternative feature classes, specifically metadata- , content-, and interaction-based options. The novelty of the projected approach lies within the characterization of users supported their interactions with their followers on condition that a user will evade options that are associated with his/her own activities, however evading those supported the followers is tough. Nineteen completely different options, as well as six recently outlined options and 2 redefined features, are known for learning 3 classifiers, namely, random forest, call tree, and Bayesian network, on a true dataset that includes benign users and spammers. The discrimination power of various feature classes is additionally analyzed, and interaction- and community-based options are determined to be the foremost effective for spam detection, whereas metadata-based options are established to be the smallest amount effective.

Social network analysis, Spammer detection, Spambot detection, Social network Security

"ADVANCED APPROACH FOR DETECTING SPAMMERS IN TWITTER", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.13-18, March-2019, Available :http://www.jetir.org/papers/JETIRAU06003.pdf

"ADVANCED APPROACH FOR DETECTING SPAMMERS IN TWITTER", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 3, page no. pp13-18, March-2019, Available at : http://www.jetir.org/papers/JETIRAU06003.pdf