Sentiment Prediction of Textual Data Using Hybrid ConvBidirectional-LSTM Model

Table 5

Accuracy comparison of the proposed model with the existing state-of-the-art models on the US airline dataset.

Authors	Model	Accuracy (%)
Wen and Li [13]	ARC	83.10
	RC	83.20
	M_ARC	83.30
Dang et al. [10]	TF-IDF-CNN	68.79
	Word embedding-CNN	82.36
	TF-IDF-RNN	61.74
	Word embedding-RNN	83.76
Umer et al. [12]	CNN-LSTM	82.00
Jain et al. [11]	LR	88.20
	NB	87.10
	DT	78.10
	SVM	80.20
	CNN	87.10
	LSTM	88.20
	CNN-LSTM	91.30
Basiri et al.[9]	ABCDM	92.75
Proposed model	GloVe-CNN-LSTM	92.79
	GloVe-HeBiLSTM	92.47
	ConvBidirectional-LSTM	93.25