Abstract
The growth of social website and electronic media contributes vast amount of user generated content such as customer reviews, comments and opinions. Sentiment Analysis term is referred to the extraction of others (speaker or writer) opinion in given source material (text) by using NLP, Linguistic Computation and Text mining. Sentiment classification of product and service reviews and comments has emerged as the most useful application in the area of sentiment analysis. This paper focuses on the comparative study (1997 – 2012) of different sentiment classification techniques performed on different data set domain such as web discourse, reviews and news articles etc. The most popular approaches are Bag of words and feature extraction used by researchers to deal with sentiment analysis of opinion related to movies, electronics, cars, music etc. The sentiment analysis is used by manufacturers, politicians, news groups, and some organization to know the opinions of customer, people, and social website users.
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