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Explainable Sentence-Level Sentiment Analysis for Amazon Product Reviews

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arxiv 2111.06070 v1 pith:GARZFXNI submitted 2021-11-11 cs.CL cs.AI

Xuechun Li , Xueyao Sun , Zewei Xu , Yifan Zhou This is my paper · ORCID
classification cs.CLcs.AI
keywords analysisattentionmodelsentimentweightsamazonaspectinterpretability
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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.

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