Implicit Polarity and Implicit Aspect Recognition in Opinion Mining

This paper deals with a double-implicit problem in opinion mining and sentiment analysis. We aim at identifying aspects and polarities of opinionated statements not consisting of opinion words and aspect terms. As a case study, opinion words and aspect terms are first extracted from Chinese hotel reviews, and then grouped into positive (negative) clusters and aspect term clusters. We observe that an implicit opinion and its neighbor explicit opinion tend to have the same aspect and polarity. Under the observation, we construct an implicit opinions corpus annotated with aspect class labels and polarity automatically. Aspect and polarity classifiers trained by using this corpus is used to recognize aspect and polarity of implicit opinions.