Machine learning-based Naive Bayes approach for divulgence of Spam Comment in Youtube station
Keywords:Artificial Intelligence, Naïve Bayes, Spam comment, QQ-plot, Ham comment
In the 21st Century, web-based media assumes an indispensable part in the interaction and communication of civilization. As an illustration of web-based media viz. YouTube, Facebook, Twitter, etc., can increase the social regard of a person just as a gathering. Yet, every innovation has its pros as well as cons. In some YouTube channels, a machine-made spam remark is produced on that recordings, moreover, a few phony clients additionally remark a spam comment which creates an adverse effect on that YouTube channel. The spam remarks can be distinguished by using AI (artificial intelligence) which is based on different Algorithms namely Naive Bayes, SVM, Random Forest, ANN, etc. The present investigation is focussed on a machine learning-based Naive Bayes classifier ordered methodology for the identification of spam remarks on YouTube
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Copyright (c) 2021 Sohom Bhattacharya, Shubham Bhattacharjee, Anup Das, Anirban Mitra , Ishita Bhattacharya , Subir Gupta
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