Paper: Fully Automatic Lexicon Expansion For Domain-Oriented Sentiment Analysis

ACL ID W06-1642
Title Fully Automatic Lexicon Expansion For Domain-Oriented Sentiment Analysis
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2006
Authors

This paper proposes an unsupervised lexicon building method for the detec- tion of polar clauses, which convey pos- itive or negative aspects in a specific domain. The lexical entries to be ac- quired are called polar atoms, the min- imum human-understandable syntactic structures that specify the polarity of clauses. As a clue to obtain candidate polar atoms, we use context coherency, the tendency for same polarities to ap- pear successively in contexts. Using the overall density and precision of co- herency in the corpus, the statistical estimation picks up appropriate polar atoms among candidates, without any manual tuning of the threshold values. The experimental results show that the precision of polarity assignment with the automatically acquired lexicon was 94% on average, and our me...