Using morphological and syntactic structures for Chinese opinion analysis

Lun Wei Ku, Ting Hao Huang, Hsin Hsi Chen

Research output: Contribution to conferencePaper

37 Scopus citations

Abstract

This paper employs morphological structures and relations between sentence segments for opinion analysis on words and sentences. Chinese words are classified into eight morphological types by two proposed classifiers, CRF classifier and SVM classifier. Experiments show that the injection of morphological information improves the performance of the word polarity detection. To utilize syntactic structures, we annotate structural trios to represent relations between sentence segments. Experiments show that considering structural trios is useful for sentence opinion analysis. The best f-score achieves 0.77 for opinion word extraction, 0.62 for opinion word polarity detection, 0.80 for opinion sentence extraction, and 0.54 for opinion sentence polarity detection.

Original languageEnglish (US)
Pages1260-1269
Number of pages10
DOIs
StatePublished - 2009
Event2009 Conference on Empirical Methods in Natural Language Processing, EMNLP 2009, Held in Conjunction with ACL-IJCNLP 2009 - Singapore, Singapore
Duration: Aug 6 2009Aug 7 2009

Conference

Conference2009 Conference on Empirical Methods in Natural Language Processing, EMNLP 2009, Held in Conjunction with ACL-IJCNLP 2009
CountrySingapore
CitySingapore
Period8/6/098/7/09

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Information Systems

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    Ku, L. W., Huang, T. H., & Chen, H. H. (2009). Using morphological and syntactic structures for Chinese opinion analysis. 1260-1269. Paper presented at 2009 Conference on Empirical Methods in Natural Language Processing, EMNLP 2009, Held in Conjunction with ACL-IJCNLP 2009, Singapore, Singapore. https://doi.org/10.3115/1699648.1699672