Paper: Dependency Tree-based Sentiment Classification using CRFs with Hidden Variables

ACL ID N10-1120
Title Dependency Tree-based Sentiment Classification using CRFs with Hidden Variables
Venue Human Language Technologies
Session Main Conference
Year 2010
Authors

In this paper, we present a dependency tree- based method for sentiment classification of Japanese and English subjective sentences us- ing conditional random fields with hidden variables. Subjective sentences often con- tain words which reverse the sentiment po- larities of other words. Therefore, interac- tions between words need to be considered in sentiment classification, which is difficult to be handled with simple bag-of-words ap- proaches, and the syntactic dependency struc- tures of subjective sentences are exploited in our method. In the method, the sentiment po- larity of each dependency subtree in a sen- tence, which is not observable in training data, is represented by a hidden variable. The po- larity of the whole sentence is calculated in consideration of interactions be...