Abstract
Short texts such as tweets and E-commerce reviews can reflect people’s opinions on interested events or products, which are much beneficial to many applications. However, one opinion word may have different sentiment polarities when modifying different targets. Therefore, in this paper we propose to extract “appraisal expressions” that are represented by tuples of (opinion word, target), indicating an opinion word and the target modified by the word. By extracting appraisal expressions, we can further construct target-sensitive sentiment dictionaries and improve the effectiveness of sentiment analysis on short texts. Consequently, we propose a filtering-refinement framework to extract appraisal expressions from short texts. In the filtering step, we extract appraisal-expression candidates, and in the refinement step, we use SVM to extract appraisal expressions and present a dependency-grammar-based approach to automatically label training data. Comparative experiments between our proposal and three baseline methods suggest the superiority and effectiveness of our proposal.
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References
Hu, M., Liu, B.: Mining and summarizing customer reviews. In: Proc. of SIGKDD, pp. 168–177 (2004)
Zheng, L., Jin, P., Zhao, J., Yue, L.: Multi-dimensional sentiment analysis for large-scale E-commerce reviews. In: Decker, H., Lhotská, L., Link, S., Spies, M., Wagner, R.R. (eds.) DEXA 2014, Part II. LNCS, vol. 8645, pp. 449–463. Springer, Heidelberg (2014)
Zhao, J., Liu, K., Wang, G.: Adding redundant features for CRFs-based sentence sentiment classification. In: Proc. of EMNLP, pp. 117–126 (2008)
Jin, W., Ho, H.H.: A novel lexicalized HMM-based learning framework for web opinion mining. In: Proc. of ACL, pp. 465–472 (2009)
Bloom, K., Garg, N., Argamon, S.: Extracting appraisal expressions. In: Proc. of HLT-NAACL, vol. 2007, pp. 308–315 (2007)
Wilson, T., Wiebe, J.: Annotating attributions and private states. In: Proceedings of the Workshop on Frontiers in Corpus Annotations II: Pie in the Sky, pp. 53–60 (2005)
Zhao, Y., Qin, B., Che, W., Liu, T.: Appraisal expression recognition with syntactic path for sentence sentiment classification. International Journal of Computer Processing of Languages 23(1), 21–37 (2011)
Kübler, S., McDonald, R., Nivre, J.: Dependency parsing. Morgan and Claypool Publishers (2009)
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Jin, P., Yu, Y., Zhao, J., Yue, L. (2015). Extracting Appraisal Expressions from Short Texts. In: Dong, X., Yu, X., Li, J., Sun, Y. (eds) Web-Age Information Management. WAIM 2015. Lecture Notes in Computer Science(), vol 9098. Springer, Cham. https://doi.org/10.1007/978-3-319-21042-1_45
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DOI: https://doi.org/10.1007/978-3-319-21042-1_45
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