Microblogging now a days became a very eminent communicating tool among internet users. Millions of users share their opinions on different aspects everyday. Thus microblogging websites play a significant role as a bundle of resources of data for opinion mining and sentiment analysis. Sentiment Analysis aims to determine the attitude of a Speaker or a writer with respect to some topic for the overall contextual polarity of the document. Sentiment Analysis is also one of the major task in Natural Language Processing (NLP). The major challenges are focused on the verge of 4 V’s (Velocity, Variety, Volume & Veracity) where the data are purely unstructured. In this paper, a particular product reviews for different companies and categories are scanned for opinion mining purposes which may further be extended to different product also. Using the corpus, we build a classifier, used to determine positive, negative & neutral sentiments for a document. A general process for sentiment polarity categorization is proposed with detailed process descriptions.