Modeling Sentiment Dependencies with Graph Convolutional Networks for Aspect-level Sentiment Classification
Table 2: Comparisons with baseline models on the Restaurant dataset and Laptop dataset. The results of baseline models are retrieved from published papers. The best results in GloVe-based models and BERT-based models are all in bold separately. -A means that the model is based on adjacent-relation graph, and -G means the model is based on global-relation graph.
['Word Embedding', 'Models', 'Restaurant Acc', 'Restaurant Macro-F1', 'Laptop Acc', 'Laptop Macro-F1']
In order to remove the influence with different word representations and directly compare the performance of different models, we compare GloVe-based models and BERT-based models separately. Our proposed model achieves the best performance on both GloVe-based models and BERT-based models, which demonstrates the effectiveness of our proposed model. In particularly, SDGCN-BERT obtains new state-of-the-art results.