Today, almost everyone is part of a socialized media, whether to express opinions on any of the products of others, business organizations, industry, educational institutions, etc., so that these views or views fluctuate they are analyzed and compared with the dictionary With the help of classifying in order to better understand whether the person who is commenting on is conducive to a positive side or a negative side and may not even support either party (neutral). Basically, the sentiment analysis is where the subjective information is extracted from the original data. The popularity of Internet users and the rapid development of emerging technologies are in parallel; active use of online commentary sites, social networks and personal blog to express their views. Through natural language processing and machine learning, with other methods for working with a lot of text along the tools, you can begin to extract the sentiments of social networks. In this article, we have discussed some of the sentiments of extraction techniques; some have taken to respond to these challenges, our approach to analyze the sentiments of social networking methods.

Behavioural analysis, Clustering, Sentiment Analysis, Social media, Tweet

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