Acknowledging discourse function for sentiment analysis

Abstract

In this paper, we observe the effects that discourse function attribute to the task of training learned classifiers for sentiment analysis. Experimental results from our study show that training on a corpus of primarily persuasive documents can have a negative effect on the performance of supervised sentiment classification. In addition we demonstrate that through use of the Multinomial Naïve Bayes classifier we can minimise the detrimental effects of discourse function during sentiment analysis. © 2014 Springer-Verlag Berlin Heidelberg.