Tracking the Corona Virus Using Sentiment Analysis on Twitter Data Application to Predict Stock Market Movements
The novel Corona Virus Decease (COVID-19) has changed the world in many aspects. The impact on the worlds’ economy is immense, and it has changed the strategies of businesses everywhere. Social media has gained more attraction, and mostly it has become a major source of information. Research needs to be conducted to understand the impact of people’s opinion written on social media on the behaviour of the stock market. Twitter has attracted researchers for studying public sentiments. In this paper, we have applied sentiment analysis and supervised machine learning principles to the tweets extracted from Twitter and analysed the correlation between stock market movements of a company and sentiments in tweets. Results indicate that there is a correlation between positive and negative tweets on COVID-19 on stock market behaviour.
Keywords: COVID-19, Sentiment Analysis, Natural language Processing, Machine learning.