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ABSTRACT
Sentiment analysis is a process of analyzing a piece of text written by a writer to identify and classify the opinions buried in that text and to determine whether the views of the writer about the topic is positive, negative, or neutral. Yelp is a review forum which provides reviews on local businesses. Users from anywhere in the world can post reviews and rate any business in this social networking site. In this paper, the textual yelp reviews of businesses are analyzed to assign a probability for the review as having positive or negative sentiment. The data considered for the sentiment analysis are the reviews on restaurants about food, service, price and ambience. Machine learning algorithms in the nltk library of python can prove to be very useful in any such research on Natural Language Processing and the library has been used extensively in this work. Each algorithm used has been analyzed and has been compared on the basis of their efficiency (confidence).
