Making the Best Use of Review Summary for Sentiment Analysis
Abstract
Sentiment analysis provides a useful overview of customer review contents. Many review websites allow a user to enter a summary in addition to a full review. Intuitively, summary information may give additional benefit for review sentiment analysis. In this paper, we conduct a study to exploit methods for better use of summary information. We start by finding out that the sentimental signal distribution of a review and that of its corresponding summary are in fact complementary to each other. We thus explore various architectures to better guide the interactions between the two and propose a hierarchically-refined review-centric attention model. Empirical results show that our review-centric model can make better use of user-written summaries for review sentiment analysis, and is also more effective compared to existing methods when the user summary is replaced with summary generated by an automatic summarization system.
Cite
@article{arxiv.1911.02711,
title = {Making the Best Use of Review Summary for Sentiment Analysis},
author = {Sen Yang and Leyang Cui and Jun Xie and Yue Zhang},
journal= {arXiv preprint arXiv:1911.02711},
year = {2020}
}
Comments
To be published in COLING-2020