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Polarity of Chinese Emotion Words: The Construction of a Polarity Database Based on Singapore Chinese Speakers

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Chinese Lexical Semantics (CLSW 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10085))

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Abstract

In this paper, we report a study of the polarity of Chinese emotion words. We conducted a large-scale polarity rating experiment with laymen speakers, and compiled a database of polarity ratings for Chinese emotion words based on these experimental results. The polarity ratings were also compared with previously reported polarity ratings, as well as related emotion word ratings such as emotion category and emotional intensity. The participants in the current study were all Singapore Chinese speakers, but the methodology and the current results will serve as an important reference for future research on sentiment analysis and emotion language in Chinese in a broader context.

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References

  1. Andreevskaia, A., Bergler, S.: Mining wordnet for a fuzzy sentiment: sentiment tag extraction from wordnet glosses. In: EACL, vol. 6, pp. 209–216 (2006)

    Google Scholar 

  2. Ding, X., Liu, B., Yu, P.S.: A holistic lexicon-based approach to opinion mining. In: Proceedings of the 2008 International Conference on Web Search and Data Mining, pp. 231–240. ACM (2008)

    Google Scholar 

  3. Esuli, A., Sebastiani, F.: Determining the semantic orientation of terms through gloss classification. In: Proceedings of the 14th ACM International Conference on Information and Knowledge Management, pp. 617–624. ACM (2005)

    Google Scholar 

  4. Hatzivassiloglou, V., McKeown, K.R.: Predicting the semantic orientation of adjectives. In: Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and 8th Conference of the European Chapter of the Association for Computational Linguistics, pp. 174–181. Association for Computational Linguistics (1997)

    Google Scholar 

  5. Kamps, J., Marx, M., Mokken, R.J., De Rijke, M.: Using wordnet to measure semantic orientations of adjectives. In: LREC, vol. 4, pp. 1115–1118 (2004)

    Google Scholar 

  6. Khoo, C., Cheon, N., Basha, J.: Comparison of lexical resources for sentiment analysis. In: Presentation at the Singapore Symposium on Sentiment Analysis. Singapore (2015)

    Google Scholar 

  7. Kim, S.M., Hovy, E.: Automatic detection of opinion bearing words and sentences. In: Companion Volume to the Proceedings of the International Joint Conference on Natural Language Processing (IJCNLP), pp. 61–66 (2005)

    Google Scholar 

  8. Lin, J., Yao, Y.: Encoding emotion in chinese: emotion type and intensity of chinese emotion words. In: Proceedings of the 16th Chinese Lexical Semantics Workshop (2015)

    Google Scholar 

  9. Strauss, G.P., Allen, D.N.: Emotional intensity and categorisation ratings for emotional and nonemotional words. Cognition and Emotion 22(1), 114–133 (2008)

    Article  Google Scholar 

  10. Turney, P.D., Littman, M.L.: Measuring praise and criticism: Inference of semantic orientation from association. ACM Transactions on Information Systems (TOIS) 21(4), 315–346 (2003)

    Article  Google Scholar 

  11. Wiebe, J.: Learning subjective adjectives from corpora. In: AAAI/IAAI, pp. 735–740 (2000)

    Google Scholar 

  12. Wilson, T., Wiebe, J., Hwa, R.: Just how mad are you? Finding strong and weak opinion clauses. In: AAAI, vol. 4, pp. 761–769 (2004)

    Google Scholar 

  13. Xu, L., Lin, H., Pan, Y., Ren, H., Chen, J.: Constructing the affective lexicon ontology. Journal of the China Society for Scientific and Technical Information 27(2), 180–185 (2008)

    Google Scholar 

  14. Xu, X., Tao, J.: Hanyu qinggan xitongzhong qinggan huafen de yanjiu [The study of affective word categorization in Chinese]. In: Proceedings of the 1st Chinese Conference on Affective Computing and Intelligent Interaction, pp. 199–205 (2003)

    Google Scholar 

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Correspondence to Yao Yao .

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Ng, C.L., Lin, J., Yao, Y. (2016). Polarity of Chinese Emotion Words: The Construction of a Polarity Database Based on Singapore Chinese Speakers. In: Dong, M., Lin, J., Tang, X. (eds) Chinese Lexical Semantics. CLSW 2016. Lecture Notes in Computer Science(), vol 10085. Springer, Cham. https://doi.org/10.1007/978-3-319-49508-8_11

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  • DOI: https://doi.org/10.1007/978-3-319-49508-8_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-49507-1

  • Online ISBN: 978-3-319-49508-8

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