A YouTube Spam Comments Detection Scheme Using Cascaded Ensemble Machine Learning Model

This paper proposes a technique to detect spam comments on YouTube, which have recently seen tremendous growth. YouTube is running its own spam blocking system but continues to fail to block them properly. Therefore, we examined related studies on YouTube spam comment screening and conducted classification experiments with six different machine learning techniques (Decision tree, Logistic regression, Bernoulli Naive Bayes, Random Forest, Support vector machine with linear kernel, Support vector machine with Gaussian kernel) and two ensemble models (Ensemble with hard voting, Ensemble with soft voting) combining these techniques in the comment data from popular music videos - Psy, Katy Perry, LMFAO, Eminem and Shakira.

Automated summary

This study proposes a technique for detecting spam comments on YouTube using various machine learning techniques and ensemble models. Experimental results show that these models can effectively screen out spam comments in the comment data of various music videos.