Spam Detection Framework for Twitter using ML
N.Noor Allema1, S. Vishnu Chaitanya2, Suman Jadam3, G.Tejaswi4
1N.Noor Allema, Assistant professor of Information technology in SRM IST, Chennai, Tamil Nadu, India.
2Suman Jadam, Department of Information Technology, SRM IST, Chennai, Tamil Nadu, India.
3S.Vishnu Chaitanya, Department of Information Technology, SRM IST, Chennai, Tamil Nadu, India.
4G.Tejaswi, Department of Information Technology, SRM IST, Chennai, Tamil Nadu, India.
Manuscript received on March 15, 2020. | Revised Manuscript received on April 01, 2020. | Manuscript published on April 10, 2020. | PP216-219 | Volume-9 Issue-6, April 2020. | Retrieval Number: F3590049620/2020©BEIESP | DOI: 10.35940/ijitee.F3590.049620
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: 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.
Keywords: Machine Learning, Spam Detection, Twitter Spam.
Scope of the Article: Patterns and frameworks