Online ISSN: 2515-8260

Keywords : Machine Language


Twitter Sentiment Analysis On Coronavirus Outbreak Using Machine Learning Algorithms

Dr K B Priya Iyer; Dr Sakthi Kumaresh

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 3, Pages 2663-2676

Social media is a source that produces massive amount of data on an unprecedented scale. It serves as a platform for every person to share their perspectives, opinions and experiences apart from just being a platform that gives information to the public who search for information on the disease. As unexpected as the occurrence of coronavirus disease 2019 (COVID-19) was, it has been radically affecting people all over the world, there is a need to analyse the opinion of people on the pandemic COVID-19. This paper focuses on the sentiment analysis of COVID-19 using twitter data. The analyses are based on the machine learning algorithms. This article provides an analysis on how people react to a pandemic outbreak, how much they are aware of the disease and its symptoms, what precautionary measures they are taking and whether or not people are following government’s guidelines etc. Understanding the posts on social media pages during a pandemic outbreak allows health agencies and volunteers to better assess and understand the public's insolences, sentiments and needs in order to deliver appropriate and effective information.