Spam Detection Framework for Twitter using ML
Assistant professor of Information technology in SRM IST,Chennai,Tamil Nadu,India., N. Noor Allema, Suman Jadam, S V Chaitanya, G. Tejaswi · International Journal of Innovative Technology and Exploring Engineering · 2020
Spam has become one of the growing issues in social media websites. Some of the users in these websites creates spam news. Coming to twitter, Users inject tweets in trending topics and replies with promotional messages providing links. A large amount of spam has been noticied in twitter. It is necessary to identify these spams tweets in a twitter stream. Now a days ,a big part of people rely on content available in social media in their decisions, so detecting and deleting these spam details is very important. A basic framework is suggested to detect malicious account holders in twitter..At present to detect these spam users or accounts there are methods which are based on content based features, Graph based features. The system which is going to be created works on machine learning based algorithms. These algorithms help to give accurate results. In this system algorithm named Naïve Bayes classifier algorithm is going to be used. This algorithm is said to be combination of many other principles relyingupon “Bayes theorem” wherein the methods share a common mode of working.