Visualization of Streaming Data Using Social Media
Social media and online social networks are playing an increasingly important role in our lives, as they attract millions of users around the world. Twitter Facebook are most popular micro blogging services, holds a special position among them, since information shared through this service spreads faster than it would have been possible with traditional sources. Now a days social networking sites are at the boom, so large amount of data is generated. Millions of people are sharing their views daily on micro blogging sites, since it contains short and simple expressions. In this paper, we will discuss about a paradigm to extract the sentiment from a famous micro blogging service such as Facebook Twitter, where users post their opinions for everything There are many interesting works analyzing the information that flows through Twitter Facebook. Most of such research focuses on post classification, i.e. what are the people talking about right now. We propose a new method to discuss the existing analysis of twitter Facebook dataset with Text mining approach such as use of Natural Language Processing Algorithm R Programming. An approach is introduced that automatically classifies the sentiments of Tweets, Posts Comments taken from Twitter Facebook dataset. These Posts or tweets are classified as positive, negative or neutral with respect to a query term of People using graph.