INFORMATIONAL FLOW ON TWITTER - CORONA VIRUS OUTBREAK – TOPIC MODELLING APPROACH

The study focuses on the information flow on twitter during the corona virus outbreak. Tweets related to #coronavirus are studied using sentiment analysis and topic modelling using Latent Dirichlet Allocation post preprocessing. The study concluded that the information flow was accurate and reliable related to corona virus outbreak with minimum misinformation. LDA analysis had identified the most relevant and accurate topics related to corona virus outbreak and sentiment analysis confirmed the prevalence of negative sentiments like fear along with positive sentiments like trust. Governments and Healthcare authorities & institutions effectively utilized to spread accurate and reliable information on twitter.