Domain dependent word polarity analysis for sentiment classification

Ho Cheng Yu, Ting Hao Huang, Hsin Hsi Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

The researches of sentiment analysis aim at exploring the emotional state of writers. The analysis highly depends on the application domains. Analyzing sentiments of the articles in different domains may have different results. In this study, we focus on corpora from three different domains in Traditional and Simplified Chinese, then examine the polarity degrees of vocabularies in these three domains, and propose methods to capture sentiment differences. Finally, we apply the results to sentiment classification with supervised SVM learning. The experiments show that the proposed methods can effectively improve the sentiment classification performance.

Original languageEnglish (US)
Title of host publicationProceedings of the 24th Conference on Computational Linguistics and Speech Processing, ROCLING 2012
Pages30-31
Number of pages2
StatePublished - Dec 1 2012
Event24th Conference on Computational Linguistics and Speech Processing, ROCLING 2012 - Chung-Li, Taiwan, Province of China
Duration: Sep 21 2012Sep 22 2012

Publication series

NameProceedings of the 24th Conference on Computational Linguistics and Speech Processing, ROCLING 2012

Conference

Conference24th Conference on Computational Linguistics and Speech Processing, ROCLING 2012
CountryTaiwan, Province of China
CityChung-Li
Period9/21/129/22/12

All Science Journal Classification (ASJC) codes

  • Language and Linguistics
  • Speech and Hearing

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    Yu, H. C., Huang, T. H., & Chen, H. H. (2012). Domain dependent word polarity analysis for sentiment classification. In Proceedings of the 24th Conference on Computational Linguistics and Speech Processing, ROCLING 2012 (pp. 30-31). (Proceedings of the 24th Conference on Computational Linguistics and Speech Processing, ROCLING 2012).