Sentiment Analysis on Twitter Data

Abstract

With the appearance of online innovation and its development, the Web presently contains an enormous measure of information for Web clients, just as a lot of information being produced. The Web has advanced into a stage for Internet learning, thought trade, and assessment sharing. Individuals utilize long-range informal communication locales, like Twitter, Facebook, and Google+ to impart and communicate their insights on different points, take an interest in conversations with assorted networks, and send messages everywhere on the world. In the subject of opinion analysis of Twitter information, a great deal of work has been finished. This examination centers on conclusion analysis of Twitter information, which is valuable for breaking down data in tweets where assessments are communicated. We use a variety of AI techniques, such as Naive Bayes and support vector machines, to investigate Twitter data streams.