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Multimedia Tools and Applications

, Volume 77, Issue 16, pp 21265–21280 | Cite as

Generate domain-specific sentiment lexicon for review sentiment analysis

  • Hongyu Han
  • Jianpei Zhang
  • Jing Yang
  • Yiran Shen
  • Yongshi Zhang
Article
  • 501 Downloads

Abstract

Lexicon-based approaches for review sentiment analysis have attracted significant attention in recent years. Lots of sentiment lexicon generation methods have been proposed. However, the generation of domain-specific lexicon with unlabeled data has not been effectively addressed. In this paper, we propose a new domain-specific sentiment lexicon generation method, mutual information is introduced to assign terms with Part-Of-Speech (POS) tags in the lexicon, the training data are selected from unlabeled corpus according to their sentiment scores which are evaluated by the SentiWordNet (SWN) based sentiment classifier. Then we propose a completed lexicon-based sentiment analysis framework which uses the domain-specific sentiment lexicon generated by the proposed domain-specific sentiment lexicon generation method. The experiment is carried out on publically available datasets. Results show that the proposed lexicon-based sentiment analysis framework using domain-specific lexicons generated by the proposed method gets a good performance.

Keywords

Lexicon-based approach Sentiment analysis SentiWordNet Mutual information 

Notes

Acknowledgements

This work is supported by the National Natural Science Foundation of China (No. 61672179, No. 61370083, No. 61402126), the Specialized Research Fund for the Doctoral Program of Higher Education (No.20122304110012), the Heilongjiang Postdoctoral Science Foundation (LBH-Z14071), the Natural Science Foundation for Young Scientists of Heilongjiang Province (QC2016083) and the Natural Science Foundation of Heilongjiang Province (F2015030).

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Hongyu Han
    • 1
  • Jianpei Zhang
    • 1
  • Jing Yang
    • 1
  • Yiran Shen
    • 1
  • Yongshi Zhang
    • 1
  1. 1.College of Computer Science and TechnologyHarbin Engineering UniversityHarbinChina

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