The explosive growth of the textual information on the web in the past few decades has brought radical change in human life. In the web, people share their opinions and views (sentiments) in many forms about products or services they are aware of. This creates a large collection of opinions and views in the form of texts, which needs to be analysed to know the efficacy of the product or service. Opinions are usually subjective expressions that describe person's sentiment, feelings towards the object or service. The sentiment can be positive or negative. This survey is a summary of the work on sentiment analysis, covering the new challenges which appear in sentiment analysis as compared to traditional fact based analysis. Currently there are four research challenges for sentiment analysis. Those are subjectivity classification, word sentiment classification, document sentiment classification and opinion extraction. This survey discusses related issues of sentiment analysis and main approaches to those problems.
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