Indian Journal of Science and Technology
DOI: 10.17485/ijst/2016/v9i45/106482
Year: 2016, Volume: 9, Issue: 45, Pages: 1-5
Original Article
Shriya Se* , R. Vinayakumar, M. Anand Kumar and K. P. Soman
Centre for Computational Engineering and Networking (CEN), Amrita School of Engineering, Coimbatore Amrita Vishwa Vidyapetham, Amrita University, Coimbatore – 641112, Tamil Nadu, India; [email protected], [email protected], [email protected], [email protected]
*Author for correspondence
Shriya Se Centre for Computational Engineering and Networking (CEN), Amrita School of Engineering, Coimbatore Amrita Vishwa Vidyapetham, Amrita University, Coimbatore – 641112, Tamil Nadu, India; [email protected]
Objective: This paper aims at classifying the Tamil movie reviews as positive and negative using supervised machine learning algorithms. Methods/Analysis: A novel machine learning approaches are needed for analyzing the Social media text where the data are increasing exponentially. Here, in this work, Machine learning algorithms such as SVM, Maxent classifier, Decision tree and Naive Bayes are used for classifying Tamil movie reviews into positive and negative. Features are also extracted from TamilSentiwordnet. Findings: The dataset for this work has been prepared. SVM algorithm performs well in classifying the Tamil movie reviews when compared with other machine learning algorithms. Both cross validation and accuracy of the algorithm shows that SVM performs well. Other than SVM, Decision tree perform well in classifying the Tamil reviews. Novelty/Improvement: SVM gives an accuracy of 75.9% for classifying Tamil movie reviews which is a good milestone in the research field of Tamil language.
Keywords: Machine Learning, Maxent Classifier, Sentimental Analysis, Support Vector Machine, Tamil Language, TamilSentiwordnet
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