Abstract
Now a day’s use of social media is increasing rapidly. People used to post their views very easily on social sites. Negativity of any person may affect society also hence people reviews are very important. Usually people use text to express their emotions on web. Sentiment Analysis is the study of human posted comments to derive an opinion to state positivity or negativity. Many techniques has been proposed for analyze sentiment from reviews or posts. Machine learning techniques like support vector machine gives better result in the field of analyze sentiment from text. Existing system uses Document level sentiment classification and Aspect level sentiment analysis. The pre processing would contain a process to eliminate repetitive words known as Stemming. Then we would have to remove illicit language and other words which do not correspond to natural language. For classification it uses Naive Bays which gives better accuracy by using rule set and classify posts or reviews into positive, negative or neutral.
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