SENTIMENTAL ANALYSIS ON COVID-19 TWITTER DATAUSING CONVOLUTIONAL NEURAL NETWORKS (CNN)

Social media in today’s world is no longer a platform to post pictures and check-ins; it has now become a platform to share views and opinions. Today the entire world is going through a very serious pandemic COVID-19. People have been sharing their views and opinions about the pandemic on social media. Twitter is the most used social media platform to share facts and opinions. Tweets from users can be used for different models and interpret results for various purposes. It becomes a very crucial task to keep analyzing what are the general views and opinions of people in this difficult time of pandemic where the entire world is going through a series of lockdowns and panic situations. In this paper, we have used dataset available online and tweets extracted by us from twitter using twitter API and have performed sentimental analysis using TextBlob and Convolutional Neural Network model(CNN) to analyze the tweets as positive, negative and neutral and have found out the accuracy attained of the model.