Combining Lexicon-Based and Learning-Based Methods for Sentiment Analysis for Product Reviews in Vietnamese Language

  • Son Trinh
  • Luu Nguyen
  • Minh Vo
Part of the Studies in Computational Intelligence book series (SCI, volume 719)


Social media websites are a major hub for users to express their opinions online. Businesses spend an enormous amount of time and money to understand their customer opinions about their products and services. Sentiment analysis which is also called opinion mining, involves in building a system to collect and examine opinions about the product made in blog posts, comments, or reviews. In this paper, we propose a framework for sentiment analysis based on combining lexicon-based and learning-based methods for product review sentiment analysis in Vietnamese language. Text analytics, Linguistic analysis and Vietnamese emotional dictionary were built, proposing features which adapted with the language was proposed. The experimental show that our system has very well performance when combine advantage of lexicon-based and learning based and can be applied in online systems for sentiment analysis product reviews.


Lexicon-based Learning-based Sentiment analysis Vietnamese Text analytics Linguistic analysis Vietnamese emotional dictionary Proposing features Product review 


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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.University of Information TechnologyHo Chi Minh CityVietnam

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