Volume 20 No 12 (2022)
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With the raised quality of online social networks, spammers realize these platforms are simple to lure users into malicious activities by posting spam messages in the comments section of the videos. In this work, YouTube comments have been taken and spam detection is performed. To stop spammers, Google Safe Browsing and YouTube Bookmaker tools detect and block spam YouTube. These tools will block malicious links, however they cannot protect the user in real-time as early as possible. Thus, industries and researchers have applied completely different approaches to form spam free social network platform. The survey for the spam comments detection methodology has been carried out using four Artificial Intelligence estimations – Logistic Regression, Ada Boost, Decision Tree and Random Forest. With the use of Neural Network, we can achieve an exactness of 91.65% and beat the present course of action by around 18%. The most notable AI procedures (Bayesian portrayal, k-NN, ANNs, SVMs) and of their suitability to the issue of spam.
KNN, ANN, SVM, AI, Ada Boost, spam
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