article

Chinese Text Sentiment Analysis Utilizing Emotion Degree Lexicon and Fuzzy Semantic Model

Authors:

Shaojian ZhuoAuthors Info & Claims

International Journal of Software Science and Computational Intelligence, Volume 6, Issue 4

Pages 20 - 32

https://doi.org/10.4018/IJSSCI.2014100102

Published: 01 October 2014 Publication History

Abstract

Text on the web has become a valuable source for mining and analyzing user opinions on any topic. Non-native English speakers heavily support the growing use of Network media especially in Chinese. Many sentiment analysis studies have shown that a polarity lexicon can effectively improve the classification consequences. Social media, where users spontaneously generated content have become important materials for tracking people's opinions and sentiments. Meanwhile, the mathematical models of fuzzy semantics have provided a formal explanation for the fuzzy nature of human language processing. This paper investigated the limitations of traditional sentiment analysis approaches and proposed an effective Chinese sentiment analysis approach based on emotion degree lexicon. Inspired by various social cognitive theories, basic emotion value lexicon and social evidence lexicon were combined to improve sentiment analysis consequences. By using the composite lexicon and fuzzy semantic model, this new sentiment analysis approach obtains significant improvement in Chinese text.

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Cited By

Luo GZhao BZhu J(2017)Improved Boosting Model for Unsteady Nonlinear Aerodynamics based on Computational IntelligenceInternational Journal of Cognitive Informatics and Natural Intelligence10.4018/IJCINI.201701010411:1(46-59)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.4018/IJCINI.2017010104

Chinese Text Sentiment Analysis Utilizing Emotion Degree Lexicon and Fuzzy Semantic Model
1. Computing methodologies
  1. Artificial intelligence
2. Hardware
  1. Power and energy
    1. Power estimation and optimization

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Published In

cover image International Journal of Software Science and Computational Intelligence

International Journal of Software Science and Computational Intelligence Volume 6, Issue 4

October 2014

81 pages

ISSN:1942-9045

EISSN:1942-9037

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IGI Global

United States

Publication History

Published: 01 October 2014

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Cited By

Luo GZhao BZhu J(2017)Improved Boosting Model for Unsteady Nonlinear Aerodynamics based on Computational IntelligenceInternational Journal of Cognitive Informatics and Natural Intelligence10.4018/IJCINI.201701010411:1(46-59)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.4018/IJCINI.2017010104

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