Performance Evaluation for Sentiment Classification of Movie Reviews |
Author(s): |
| Shinija S , St. Joseph's College of Engineering; Mrs. P. Kalaivani, St. Joseph's College of Engineering |
Keywords: |
| Sentiment Analysis, Neural Network Learning, Feature Selection, Feature Reduction, Support Vector Machine, Naïve Bayes |
Abstract |
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Sentiment Analysis focuses on analyzing the movie review extracted from online media which helps in understanding the public opinion about the product and utilizing it for future enhancement of business. Information Gain (IG) and principal component analysis (PCA) are used to reduce the dimensionality of different combination of feature vector and combines with learning algorithm to learn the sentiment classifier to improve the performance based on accuracy, precision and recall. In this paper, we consider three classification algorithms such as Support Vector, Naïve Bayes and Neural Network are used to provide accuracy for different combination of IG and PCA for different feature vector and find out which classifier provides good performance based on accuracy, precision, recall and F- Measure. |
Other Details |
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Paper ID: IJSRDV4I30196 Published in: Volume : 4, Issue : 3 Publication Date: 01/06/2016 Page(s): 1537-1542 |
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