The digital community paves the way for huge volume of opinion rich reviews from forums, blogs, discus-sions and so on. In divergence with common text classification approach, word count in the document are used as features. Metalevel features are taken from hand labeled Tamil movie reviews. Once the feature is extracted, they are used as input for supervised machine learning algorithms for further classification. Generally the frequency of occurrence of keyword is more suitable feature in overall sentiment analysis and not necessarily indicated by repeated use of keywords. Experimental results point out the proposed method in this paper which shows considerable accuracy in detecting sentimental information in Tamil. Accuracy of about 65. © Research India Publications.
S. J. Arunselvan, M. Kumar, A., and Soman, K. P., “Sentiment analysis of tamil movie reviews via feature frequency count”, International Journal of Applied Engineering Research, vol. 10, no. 20, pp. 17934-17939, 2015.