Table 15.

Performance comparison of the proposed model with state-of-art models.

Model	F1-score	Accuracy
Random Forest Classifier	81.58	82.06
SVM Classifier	82.71	82.04
CNN	83.73	83.06
BERT	88.97	89.10
DistilBERT	89.08	88.40
RoBERTa [3]	89.18	89.50
RoBERTa + MLP [43]	90.05	90.30
CT-BERT model [41]	90.96	91.40
CT-BERT + RoBERTa [40]	90.96	91.50
Proposed Model(MVEDL)	91.14	91.75