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Multi-Entity Aspect-Based Sentiment Analysis with Context, Entity, Aspect Memory and Dependency Information

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Published:07 May 2019Publication History
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Abstract

Fine-grained sentiment analysis is a useful tool for producers to understand consumers’ needs as well as complaints about products and related aspects from online platforms. In this article, we define a novel task named “Multi-Entity Aspect-Based Sentiment Analysis (ME-ABSA)”. It investigates the sentiment towards entities and their related aspects. It makes the well-studied aspect-based sentiment analysis a special case of this type, where the number of entities is limited to one. We contribute a new dataset for this task, with multi-entity Chinese posts in it. We propose to model context, entity, and aspect memory to address the task and incorporate dependency information for further improvement. Experiments show that our methods perform significantly better than baseline methods on datasets for both ME-ABSA task and ABSA task. The in-depth analysis further validates the effectiveness of our methods and shows that our methods are capable of generalizing to new (entity, aspect) combinations with little loss of accuracy. This observation indicates that data annotation in real applications can be largely simplified.

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  1. Multi-Entity Aspect-Based Sentiment Analysis with Context, Entity, Aspect Memory and Dependency Information

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    • Published in

      cover image ACM Transactions on Asian and Low-Resource Language Information Processing
      ACM Transactions on Asian and Low-Resource Language Information Processing  Volume 18, Issue 4
      December 2019
      305 pages
      ISSN:2375-4699
      EISSN:2375-4702
      DOI:10.1145/3327969
      Issue’s Table of Contents

      Copyright © 2019 ACM

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 7 May 2019
      • Accepted: 1 February 2019
      • Revised: 1 January 2019
      • Received: 1 October 2018
      Published in tallip Volume 18, Issue 4

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