Effectiveness of SVM kernel for YOUTUBE Comment Filtering
Shailender Kumar, Shweta Gupta · 2022
The impact of Social networking platform is evident in each generation and almost all fields. It made many tasks more convenient that was not possible earlier. YouTube is one such platform. It can be utilized as a source of entertainment, discussion portal, information sharing, knowledge gathering. Various newborn and popularly known organizations display their advertisements over the platform as short video or links in comment section that help content creators of the video through some financial gains. These advertisements can be greatly helpful to visitors and firm. Also the comment section may contain some cogitative discussions. With all such activities found on the platform some spiteful ones are also lurking over it. Spammers used to suffuse malicious links and data over the platform. In this study, we directed towards the comment section of the platform and executed a comparative analysis of different SVM kernels for the classification of Spam or ham comments over the YouTube application. We also studied the impact of feature extraction incorporating two feature extraction techniques Tf-Idf and BOW.