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Computing Sentiment Scores of Adjective Phrases for Vietnamese

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Multi-disciplinary Trends in Artificial Intelligence (MIWAI 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10053))

Abstract

Building sentiment lexicons is an essential task that provides “material” for all sentiment analysis levels: document-based, sentence-based, and aspect-based. For Vietnamese researchers, this problem is still a hot issue and should be resolved because the Vietnamese sentiment corpus is not complete. In this paper, we propose a fuzzy language computation based on Vietnamese linguistic characteristics to provide an effective method for computing the sentiment polarity of adjective phrases. Then, from this base, we built a sentiment phrase dictionary for Vietnamese with fine-grained scores. In our experiments on a real data set, we show that our approach gives perfectly acceptable results.

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Notes

  1. 1.

    http://vdict.com.

  2. 2.

    https://translate.google.com/.

  3. 3.

    https://www.agoda.com/vi-vn.

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Acknowledgment

This paper was supported by the research project C2016-20-32 funded by Vietnam National University Ho Chi Minh City (VNU-HCM).

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Authors and Affiliations

  1. Faculty of Computer Science and Engineering, Ho Chi Minh City University of Technology, Ho Chi Minh City, Vietnam

    Thien Khai Tran & Tuoi Thi Phan

Authors
  1. Thien Khai Tran
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  2. Tuoi Thi Phan
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Corresponding author

Correspondence to Thien Khai Tran .

Editor information

Editors and Affiliations

  1. Mahasarakham University , Maha Sarakham, Thailand

    Chattrakul Sombattheera

  2. Harz University of Applied Sciences , Wernigerode, Germany

    Frieder Stolzenburg

  3. University of Science and Technology , Hong Kong, China

    Fangzhen Lin

  4. Macquarie University , North Ryde, New South Wales, Australia

    Abhaya Nayak

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Tran, T.K., Phan, T.T. (2016). Computing Sentiment Scores of Adjective Phrases for Vietnamese. In: Sombattheera, C., Stolzenburg, F., Lin, F., Nayak, A. (eds) Multi-disciplinary Trends in Artificial Intelligence. MIWAI 2016. Lecture Notes in Computer Science(), vol 10053. Springer, Cham. https://doi.org/10.1007/978-3-319-49397-8_25

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  • DOI: https://doi.org/10.1007/978-3-319-49397-8_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-49396-1

  • Online ISBN: 978-3-319-49397-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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