Paper: Using Morphological and Syntactic Structures for Chinese Opinion Analysis

ACL ID D09-1131
Title Using Morphological and Syntactic Structures for Chinese Opinion Analysis
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2009
Authors

This paper employs morphological struc- tures and relations between sentence seg- ments 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 po- larity detection. To utilize syntactic struc- tures, we annotate structural trios to repre- sent relations between sentence segments. Experiments show that considering struc- tural trios is useful for sentence opinion analysis. The best f-score achieves 0.77 for opinion word extraction, 0.62 for opin- ion word polarity detection, 0.80 for opin- ion sentence extraction, and 0.54 for opin- ion sentence polarity detection...