Negation disambiguation using the maximum entropy model

Abstract

Handling negation issue is of great significance for sentiment analysis. Most previous studies adopted a simple heuristic rule for sentiment negation disambiguation within a fixed context window. In this paper we present a supervised method to disambiguate which sentiment word is attached to the negator such as “(not)” in an opinionated sentence. Experimental results show that our method can achieve better performance than traditional methods.