Sentiment Analysis through Twitter Feeds

Abstract

The purpose of this project is to perform Natural Language processing (NLP) on twitter data in order to have some beneficial infonnation that can be helpful to different organizations. Sentiment Analysis is for extracting Sentiments (positive, negative, or neutral) from a collection of data. All this process includes data extraction, preprocessing and some appropriate algoritlm1s' implementation to achieve helpful results. Accurate results of the performed analysis can offer numerous applications m many fields of life. E.g. Voting Advise Applications, Detect early warning system of possible disruption in a timely manner by detecting early feedback from citizens. Helpful not only for policy makers but also for nonanal human beings who can now easily understand the outcome of some discussion and can participate in it as well. Sentiment Analysis can also be used for the purpose of requirement gathering, regarding any project before its initiation. It is widely applied to reviews and social media for a variety of applications, rang from marketing to customer service.