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CT-SPA: Text sentiment polarity prediction model using semi-automatically expanded sentiment lexicon
Proceedings of the Eighth SIGHAN Workshop on Chinese Language Processing
In this study, an automatic classification method based on the sentiment polarity of text is proposed. This method uses two sentiment dictionaries from different sources: the Chinese sentiment dictionary CSWN that integrates Chinese WordNet with SentiWordNet, and the sentiment dictionary obtained from a training corpus labeled with sentiment polarities. In this study, the sentiment polarity of text is analyzed using these two dictionaries, a mixed-rule approach, and a statistics-baseddoi:10.18653/v1/w15-3125 dblp:conf/acl-sighan/ChangLCW15 fatcat:vhtugn4ht5gudjazvzlwsjo6x4