Multi-task BERT for Aspect-based Sentiment Analysis

Yuqi Wang, Qi Chen, Wei Wang

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

10 Citations (Scopus)

Abstract

Social media data are increasingly used for smart computing applications, e.g., social event detection and sentiment analysis. Sentiment analysis, an important natural language processing task, has been applied in many real-world applications such as recommender systems and intelligence business systems. To process such social media data, natural language processing techniques such as BERT can be applied to extract essential language representations and produce state-of-the-art results. In this paper, we utilize the pre-trained BERT model as the backbone network and propose the BERT-SAN model to perform aspect-based sentiment analysis. The result demonstrates that our proposed model has a significant improvement against other baselines.

Original languageEnglish
Title of host publicationProceedings - 2021 IEEE International Conference on Smart Computing, SMARTCOMP 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages383-385
Number of pages3
ISBN (Electronic)9781665412520
DOIs
Publication statusPublished - Aug 2021
Event7th IEEE International Conference on Smart Computing, SMARTCOMP 2021 - Virtual, Irvine, United States
Duration: 23 Aug 202127 Aug 2021

Publication series

NameProceedings - 2021 IEEE International Conference on Smart Computing, SMARTCOMP 2021

Conference

Conference7th IEEE International Conference on Smart Computing, SMARTCOMP 2021
Country/TerritoryUnited States
CityVirtual, Irvine
Period23/08/2127/08/21

Keywords

  • Aspect-Based Sentiment Analysis
  • BERT
  • Natural Language Processing

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