Spam Detection on Social Media Platform

Abstract

Social Media has become an essential platform for communication and information sharing. With its widespread popularity, the problem of spam has also become increasingly common. In this paper, we propose an effective machine learning- based approach for spam detection on social media. Our approach uses various features and classifiers to distinguish spam messages from legitimate ones. The features used include lexical, syntactic, and semantic features, while the classifiers used include decision trees, naive Bayes, and support vector machines. Our experimental results demonstrate that the proposed approach outperforms existing spam detection methods on social media.