Before revision:  Our experimental evaluation shows that with appropriate pre-processing techniques  , Multinomial Logistic Regression (MLR) achieves the best F1-score of 64.40  %DIF < , a significant improvement of 4.66\\% over the CNN model built by the authors of UIT-VSMEC (59.74\\%).abstract 
After revision:  Our experimental evaluation shows that with appropriate pre-processing techniques , Multinomial Logistic Regression (MLR) achieves the best F1-score of 64.40  %DIF < , a significant improvement of 4.66\\% over the CNN model built by the authors of UIT-VSMEC (59.74\\%).abstract \%, a significant improvement of 4.66\% over the CNN model built by the authors of UIT-VSMEC (59.74\%).