In this paper, we conduct a sentence level sentiment analysis on the product reviews from Amazon and thorough analysis on the model interpretability. For the sentiment analysis task, we use the BiLSTM model with attention mechanism. For the study of interpretability, we consider the attention weights distribution of single sentence and the attention weights of main aspect terms. The model has an accuracy of up to 0.96. And we find that the aspect terms have the same or even more attention weights than the sentimental words in sentences.
翻译:在本文中,我们对亚马逊产品审查进行判决级情绪分析,对模型可解释性进行透彻分析。在情感分析任务中,我们使用BILSTM模型的注意机制。在可解释性研究中,我们考虑了单句的注意权重分布和主要术语的注意权重。模型的准确性高达0.96,我们发现,侧面术语的注意权重与句中伤感词的注意权重相同或甚至更高。