Sentiment Classification of User Reviews Using Supervised Learning Techniques with Comparative Opinion Mining Perspective

Abstract

Comparative opinion mining has received considerable attention from both individuals and business companies for analyzing public feedback about the competing products. The user reviews about the different products posted on social media sites, provide an opportunity to opinion mining researchers to develop applications capable of performing comparative opinion mining on different products. Therefore, it is an important task of investigating the applicability of different supervised machine learning algorithms with respect to classification of comparative reviews. In this work different machine learning algorithms are applied for performing multi-class classification of comparative user reviews into different classes. The results show that Random Forest outperforms amongst all other classifiers used in the research.