Abstract
With the thriving of microblog, a huge amount of people get involved in online life. This leads the government to intensify supervision on online remarks, and opinion polarity is what they care most. But microblog opinions contain several specialties from hotel remarks; they are format-free, short, and most express only one polarity. In this paper, we target on finding an appropriate polarity recognition method for public opinion supervision system. In our method, we explore new feature extraction rules which extract phizs, emotional nouns, verbs, adjectives, and bigrams as representative features. Then, we apply SVM to classify these online opinions into positive and negative class. Based on the crawled real-world datasets, our method can respectively achieve an accuracy of 80.1% and 87.4% for microblog reviews and traditional hotel remarks, so the proposed method is appropriate and effective for public opinion supervision system.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Hatzivassiloglou, V., Mckeown, K, R.: Predicting the semantic orientation of adjectives[A]. In: Proceedings of 21st Conference of the American Association for Artificial Intelligence (AAAI-04)[C], pp. 174–181 (1997)
Turney, P., Littman, M.: Measuring praise and criticism, Inference of semantic orientation from association[J]. ACM Trans. Info. Syst. 21(4), 315–316 (2003)
Wiebe, J., Riloff, E.: Creating subjective and objective sentence classifiers from unannotated text. In: Proceedings of CICLING (2005)
Pang, B., Lee, L., Vaithyanathan, S.: Thumbs up? Sentiment classification using machine learning techniques. In: Proceedings of EMNLP (2002)
Wilson, T., Wiebe, J., Hoffmann, P.: Recognizing Contextual Polarity in Phrase-Level Sentiment Analysis, HLT-EMNLP (2005)
Liu, Q., Li, J.-S.: Word similarity computing based on HowNet[c]. In: The 3rd Chinese Lexical Semantics Workshop, Taipei (2002)
Thet, T.T., Na, J.-C., Khoo, C.S.G.: Aspect-based sentiment analysis of movie reviews on discussion boards. J. Info. Sci. 36(6), 823–848 (2010)
Acknowledgements
The work was supported by Guangdong Natural Science Foundation (No.9451805702004046) and the cooperation project in industry, education, and research of Guangdong province and Ministry of Education of P.R.China (No.2010B090400527). In addition, we thank the anonymous reviewers for their careful reading and very valuable comments and suggestions.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer Science+Business Media New York
About this paper
Cite this paper
Zeng, M., Yang, Y., Liu, W. (2013). An Approach of Text Sentiment Analysis for Public Opinion Monitoring System. In: Li, J., Qi, G., Zhao, D., Nejdl, W., Zheng, HT. (eds) Semantic Web and Web Science. Springer Proceedings in Complexity. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6880-6_11
Download citation
DOI: https://doi.org/10.1007/978-1-4614-6880-6_11
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-6879-0
Online ISBN: 978-1-4614-6880-6
eBook Packages: Computer ScienceComputer Science (R0)