SOCIAL MEDIA ANALYSIS WITH AI: SENTIMENT ANALYSISTECHNIQUES FOR THE ANALYSIS OF TWITTER COVID-19 DATA
Rijwan Khan, Piyush Shrivastava, Aashna Kapoor, Aditi Tiwari, Abhyudaya Mittal
Abstract
Recently, In the current situation there has been an outbreak known as COVID-19 (corona virus) causing acute respiratory syndrome, first noticed in China and now a pandemic. Social media plays a crucial role in the current scenario of the world being locked up and further leading to the social imbalance among people. The news scattered like leaves about people attempting suicide. In this chapter, we aim at providing the sentiment analysis on covid-19, about the people's reaction towards the decisions made either by the government or the local authorities through Twitter. We propose a system which automates analyzing the tweets and categorizing them into positive, negative or neutral sets. With the utilization of automata and NLP (natural language processing) together the accuracy, quantization and prediction of the sets can be achieved. Classification can be whether on a pattern based or a NLTK (Natural language toolkit). The classified results are further stored in the structures that could be iterated while calling for the visualization.