SENTIMENTAL DATA ANALYSIS ON SOCIAL MEDIA

Social network is one of the admired communication medium and serves as the platform for tracking and analyzing public sentiment of various people on different domains or products. With the explosive growth of user generated messages, Twitter and Facebook has become a social site where millions of users can exchange their opinion. Sentiment analysis affords as an economical and effective way to expose public opinion timely, which is critical for decision making in various domains. Similarly, due to the large volume of opinions, rich web resources such as discussion forum, review sites, blogs and news etc are available in digital form; much of the current research is focusing on the area of sentiment analysis. The information is very useful for businesses for marketing, governments and individuals. While this content meant to be helpful, analyzing the bulk of user generated content is difficult and time consuming. In the existing system there is no way of analysis and ranking the user opinions and sometimes they consider the individual opinions without conducting any reviews. But in proposed there is a need to develop an intelligent system which automatically extract such huge content and classify them into positive, negative and neutral type using Artificial Neural Networks based on the specified criteria.