Abstract Opinion mining or sentiment analysis is to identify and classify the sentiments/opinion/emotions from text. Over the last decade, in addition to english language, many indian languages include interest of research in this field. For this paper, we compared many approaches developed till now and also reviewed previous researches done in case of indian languages like telugu, Hindi and Bengali. We developed a hybrid system for Sentiment analysis of Punjabi text by integrating subjective lexicon, N-gram modelling and support vector machine. Our research includes generation of corpus data, algorithm for Stemming, generation of punjabi subjective lexicon, developing Feature set, Training and testing support vector machine. Our technique proves good in terms of accuracy on the testing data. We also reviewed the results provided by previous approaches to validate the accuracy of our system.

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