Tinkhomo ticala kubanemndlandla wekulala natineminyaka lemitsatfu ngebudzala, bese titfola litfole lekucala kuwo lomnyaka wesitsatfu. Emva kwekumitsa emalanga lamakhulu lamabili nemashumi lasikhombisa abese atala litfole lelikala 17 kg nalicedvwa kutalwa. 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. More »»