Abstract
Social networking sites these days are great source of communication for internet users. So these are important source for understanding the emotions of people. In this paper, we use data mining techniques for the purpose of classification to perform sentiment analysis on the views people have shared in Twitter. We collect dataset, i.e. The tweets from twitter that are in natual language and apply text mining techniques -- tokenization, stemming etc to convert them into useful form and then use it for building sentiment classifier that is able to predict happy, sad and neutral sentiments for a particular tweet. Rapid Miner tool is being used, that helps in building the classifier as well as able to apply it to the testing dataset. We are using two different classifiers and also compare their results in order to find which one gives better results.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
