Applying Three-way Decisions to Sentiment Classification with Sentiment Uncertainty

Sentiment uncertainty is a key problem of sentiment classification. In this paper, we mainly focus on two issues with sentiment uncertainty, i.e., context-dependent sentiment classification and topic-dependent sentiment classification. This is the first work that applies three-way decisions to sentiment classification from the perspective of the decision-theoretic rough set model. We discuss the relationship between sentiment classification rules and thresholds involved in three-way decisions and then prove it. The experiment results on real data sets validate that our methods are satisfactory and can achieve better performance.