Document sentiment classification using hybrid wavelet methodologies

Abstract

Sentiment and semantic analysis of a text are very important issues of today because of increasing text data. Our study proposes a new method to reveal the hypernym relations (generic term) of the words in the text and to enhance the accuracy results of sentiment classification of the texts. We used wavelet transform method that has been rarely used in text analysis. In our study, the aim is to show how this method contributes the sentiment analysis classification problem. We used classical algorithms and hybrit wavelet algorithm for sentiment analysis problem. It has been observed that when wavelets are applied to classical classification algorithms, the accuracies increased approximately 5%.