A Framework for Measuring Emotional Responses of Individuals in Social media by using Big data Approach

Big data analytics examines large amounts of data to uncover hidden patterns, correlations and other insights. It is possible to analyze the data and get answers immediately with today's technology. Sentimental Analysis is used to analyze opinions of the individual or group related to a business, product or service. Sentimental analytics is often driven by an algorithm along with voice inflection to identify the feelings of people regarding the topic. Also, the amount stress in the customer’s voice and how fast they are speaking. In social media, the difficulties faced by the analyst is language most of the people doesn’t use the proper format (like how r u,gud mrg etc.,). To overcome such situation sentimental analytics device uses the Natural Language Processor (NLP). Another difficulty is if a word that actually carries the positive meaning but due to sarcastic manner could easily be misinterpreted. The paper mainly focuses on analysis of the text of the individual’s emotions like joy, surprise, anger, disgust, positive and negative in social media and offers the result.