Analysing COVID-19 News Impact on Social Media Aggregation

Abstract

The pandemic coronavirus so called COVID-19 outbreak, which was recognized in late 2019, requires special consciousness because of its future epidemics and possible worldwide menace. Besides its clinical approaches and treatments. As Artificial Intelligence (AI) assures a new prototype for healthcare. There are various AI tools that are built upon Machine Learning (ML) algorithms are included to examine the data and decision-making processes. People spend many hours every-day on social media websites to share their views, ideas, opinions, and expressions with others, so in this paper, I have analysed the sentiments on reddit news regarding coronavirus disease(COVID-19) jeopardy, because most of the peoples from various countries are affected by coronavirus that is very condemnatory issue at present days, so analyze the sentiments of various people's opinion for this disease, we are fetching the reddit streaming articles connected to coronavirus using reddit API and scrutinized these articles using machine learning methods and tools as positive, negative and neutral. In this paper, I have run experiments through Python programming on various articles related to pandemic corona virus using reddit API and NLTK library is used for pre-processing of articles and then scrutinizing the articles dataset by using Textblob and it pointers to stimulating outcomes as positive, negative, neutral sentiments over different conceptions. The outcomes show that on reddit related to COVID-19 articles about 50% percentage articles are neutral, 22% articles are positive and about 28 % was negative.