An Approach for Spam Detection in YouTube Comments Based on Supervised Learning
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In the recently advanced society, online social media sites like YouTube, Twitter, Facebook, LinkedIn, etc are very popular. People turn to social media for interacting with other people, gaining knowledge, sharing ideas, for entertainment and staying informed about the events happening in the rest of the world. Among these sites, YouTube has emerged as the most popular website for sharing and viewing video content. However, such success has also attracted malicious users, which aim to self-promote their videos or disseminate viruses and malware. These spam videos may be unrelated to their title or may contain pornographic content. Therefore, it is very important to find a way to detect these videos and report them. In this work, we have evaluated several top-performance classification techniques for such purpose. The statistical analysis of results indicates that the Multilayer Perceptron and Support Vector Machine show good accuracy results.
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