The Efficient Process that is analyzing Sentiment is the way of identifying the orientation of opinion in text data. It finds assignment of comments whether it become positive comment or negative comment to perform analysis of review collected from social networking sites. Now a days Use of Social networking sites are going to increase rapidly. In various Micro blogging sites user post their review about any interesting topics about event, about newly launched product, etc. according to that user going to analyze reviews. In this paper we put forward process of analyzing sentiment that is also called as Opinion mining on collected twitter review data set on mobile product based on priority wise selection of feature. By considering this concept we are going to assign polarity to the word which decide polarity of comments and based on that we divide the comments into positive and negative club. For that classification we use machine learning Naive Bayes algorithm and according to that we analyze quality of that product and decide whether to purchase product or not based on selected feature of product.

Machine learning, Naive Bayes, opinion mining, Sentiment analysis

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