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Computer Science > Computation and Language

arXiv:1911.02711 (cs)
[Submitted on 7 Nov 2019 (v1), last revised 29 Oct 2020 (this version, v2)]

Title:Making the Best Use of Review Summary for Sentiment Analysis

Authors:Sen Yang, Leyang Cui, Jun Xie, Yue Zhang
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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.
Comments: To be published in COLING-2020
Subjects: Computation and Language (cs.CL)
Cite as: arXiv:1911.02711 [cs.CL]
  (or arXiv:1911.02711v2 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.1911.02711

Submission history

From: Sen Yang [view email]
[v1] Thu, 7 Nov 2019 01:46:54 UTC (1,835 KB)
[v2] Thu, 29 Oct 2020 07:15:01 UTC (3,130 KB)
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