Analysis and evaluation of Feature selectors in opinion mining

Abstract

Computational performance is improved by use of basic feature selection in most of the research works. Sentiment analysis identifies whether opinion expressed on a topic in a document is positive or negative. But many potential sentiment analysis applications are not feasible because of the voluminous amount of features present in the corpus. This paper evaluates a range of feature selectors systematically with respect to their efficiency in improving the performance of the classifiers for sentiment analysis. Movie reviews are used for sentiment analysis in this study.