CONTEXT BASED SENTIMENT ANALYSIS OF TWITTER USING HADOOP FRAMEWORK

People often care for the opinions of others that is where sentiment analysis plays a huge role in analysis how many have positive or good impression on a particular product or object or anything and how many have a negative or bad impression on it. So this sentiment analysis can be made use by those people who give importance to others opinion. As there is a rapid development in technology, social media became a great platform for people to share ideas, views, consult for reviews. This information is used for many purposes, one of them is sentiment analysis. Sentiment Analysis or opinion mining is the process of collecting users' opinion from user generated content. It is used to determine whether a piece of text, word, sentence is positive, negative or neutral. Sentiment analysis provides a very accurate analysis of the overall emotion of the text content incorporated from sources like blogs, articles, forums, consumer reviews, surveys, twitter etc. The opinion is used as data in sentiment analysis. Sentiment Analysis can be widely applied to reviews and social media for a variety of applications ranging from marketing to customer service. It has various applications such as cricket score or win predictions, stock market prediction, product review collection, political predictions based on the sentiments of the people. A number of methods are available for analysis and classification of data.