Sentiment analysis (SA) is an intellectual process of extricating user's feelings and emotions. It is one of the pursued field of Natural Language Processing (NLP). The evolution of Internet based applications has steered massive amount of personalized reviews for various related information on the Web. These reviews exist in different forms like social Medias, blogs, Wiki or forum websites. Both travelers and customers find the information in these reviews to be beneficial for their understanding and planning processes. The boom of search engines like Yahoo and Google has flooded users with copious amount of relevant reviews about specific destinations, which is still beyond human comprehension. Sentiment Analysis poses as a powerful tool for users to extract the needful information, as well as to aggregate the collective sentiments of the reviews. Several methods have come to the limelight in recent years for accomplishing this task. In this paper we compare the various techniques used for Sentiment Analysis by analyzing various methodologies.

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