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International Journal of Soft Computing And Artificial Intelligence (IJSCAI)-IJSCAI
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Volume-2,Issue-1  ( May, 2014 )
Paper Title
Sentiment Analysis Of Restaurant Reviews Using Hybrid Classification Method
Author Name
M. Govindarajan
Assistant Professor, Department of Computer Science and Engineering, Annamalai University, Annamalai Nagar, Tamil Nadu, India
Abstract— The area of sentiment mining (also called sentiment extraction, opinion mining, opinion extraction, sentiment analysis, etc.) has seen a large increase in academic interest in the last few years. Researchers in the areas of natural language processing, data mining, machine learning, and others have tested a variety of methods of automating the sentiment analysis process. In this research work, new hybrid classification method is proposed based on coupling classification methods using arcing classifier and their performances are analyzed in terms of accuracy. A Classifier ensemble was designed using Naïve Bayes (NB), Support Vector Machine (SVM) and Genetic Algorithm (GA). In the proposed work, a comparative study of the effectiveness of ensemble technique is made for sentiment classification. The feasibility and the benefits of the proposed approaches are demonstrated by means of restaurant review that is widely used in the field of sentiment classification. A wide range of comparative experiments are conducted and finally, some in-depth discussion is presented and conclusions are drawn about the effectiveness of ensemble technique for sentiment classification.
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