Distribution Of Emotional Reactions To New Headlines In Twitter Using Machine Learning Approaches and Naive Bayes classifier

Abstract

In today’s world there are so much micro blogging sites, among all twitter is one of the popular site. It has become an important part for all individuals, politicians, companies, celebrities, etc. Almost all the major news outlets have Twitter account where they post news headlines for their followers. People with Twitter accounts can reply or retweet the news headlines. Twitter users who have an account can also post news headlines from any other news outlets. When people post, reply or retweet news posts on Twitter, it is obvious that they are expressing their sentiments through that. The main aim of the project is to extract subjectivity of opinions of people about particular news in Twitter. Specially, the interest is in determining the sentiment of Twitter posts about particular news. This project Explores Naïve Bayes Classifier for textual classification and various twitter-specific sentiment analysis studies applied to Twitter data and their Outcomes.