Embedding | Classifier | Accuracy | Precision | Recall | AUC | F1-score |
---|---|---|---|---|---|---|
Word2Vec | CNN | 0.729 | 0.744 | 0.729 | 0.767 | 0.733 |
 | MLP | 0.644 | 0.643 | 0.644 | 0.711 | 0.644 |
 | Bi-LSTM | 0.737 | 0.740 | 0.737 | 0.677 | 0.738 |
 | Bi-LSTM-CNN | 0.728 | 0.729 | 0.728 | 0.692 | 0.728 |
BERT | CNN | 0.770 | 0.788 | 0.777 | 0.908 | 0.781 |
 | MLP | 0.719 | 0.714 | 0.719 | 0.874 | 0.712 |
 | Bi-LSTM | 0.777 | 0.792 | 0.780 | 0.888 | 0.774 |
 | Bi-LSTM-CNN | 0.698 | 0.696 | 0.698 | 0.861 | 0.690 |
 | Fine-tune | 0.760 | 0.761 | 0.759 | 0.868 | 0.760 |
 | IDPT | 0.842 | 0.843 | 0.842 | 0.948 | 0.841 |
BERT-wmm-ext | Fine-tune | 0.756 | 0.756 | 0.756 | 0.883 | 0.754 |
Mengzi | Fine-tune | 0.751 | 0.751 | 0.751 | 0.846 | 0.750 |
Roberta | Fine-tune | 0.767 | 0.767 | 0.767 | 0.878 | 0.764 |