In today’s digital world tremendous growth of information on Social media is raising day by day, It has become a platform for the users to express their sentiments in the form of blogs, feedback, polls etc. On the other hand, it is very hard to group the data for the users opinion because of time consumption and analysising. Such data are classified and categorization into polarities like positive, negative and neutral process using sentiment analysis and processed for the data accuracy. A model can be built by contrasting classification and clustering techniques. In this process, duplicate attributes of data is removed and the best classification of data accuracy can be achieved.
Volume 11 | 02-Special Issue
Pages: 1668-1674