• DocumentCode
    3562489
  • Title

    An empirical study on sentiment analysis for Vietnamese

  • Author

    Nguyen Thi Duyen ; Ngo Xuan Bach ; Tu Minh Phuong

  • Author_Institution
    Dept. of Comput. Sci., Posts & Telecommun. Inst. of Technol., Hanoi, Vietnam
  • fYear
    2014
  • Firstpage
    309
  • Lastpage
    314
  • Abstract
    This paper presents an empirical study on machine learning based sentiment analysis for Vietnamese, in which we focus on the task of sentiment classification. We investigate the task regarding both learning model and linguistics feature aspects. We also introduce an annotated corpus for sentiment classification extracted from hotel reviews in Vietnamese and conduct a series of experiments and analyses on that corpus. The paper provides useful information for further research as well as for building a real sentiment analysis system for Vietnamese.
  • Keywords
    learning (artificial intelligence); natural language processing; pattern classification; Vietnamese; annotated corpus; hotel reviews; learning model; linguistics feature aspects; machine learning; sentiment analysis; sentiment classification; Accuracy; Entropy; Feature extraction; Learning systems; Sentiment analysis; Support vector machines; Training; Maximum Entropy Models; Naive Bayes; Sentiment Analysis; Support Vector Machines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Technologies for Communications (ATC), 2014 International Conference on
  • Print_ISBN
    978-1-4799-6955-5
  • Type

    conf

  • DOI
    10.1109/ATC.2014.7043403
  • Filename
    7043403