Leveraging the Ensemble Model in Spam detection for Youtube Comments

YouTube (YuTe) spam replies have lately shown an explosive increase, and this research presents a method to identify them. YuTe uses its trojan technology, although it hasn't been effective so far. For this reason, the authors of this research looked at prior research on YuTe spamming remark filtering and ran trials on remark information from four different types of famous Telugu music videos (melody, classical, rock, and duet) to see how well E-GARCH+ARIMA performed as classification techniques. Therefore, this article will use the Hybrid time-series predictive ARIMA (Autoregressive Integrated Moving Average)+ E-GARCH (Exponential Generalized Auto-Regressive Conditional Heteroskedasticity) to anticipate spam identification in Yute music videos. When compared to both standalone simulations and cutting-edge hybrid methods, the aforementioned hybrid ARIMA+E-GARCH paradigm fared better across the board for RMSE, MAE, and MSE.