Affiliation:
1. Indian Institute of Information Technology, Nagpur, India
Abstract
The COVID-19 pandemic has affected the daily life of each individual drastically at global level. The adverse effects of the pandemic on an individual and people around them have created an anxious and depressive environment. The virus has changed the way of living for most people and increased the distance between individuals. As the COVID-19 spread, people have been constantly in bad mental health which includes fear, boredom, sadness, and stress. Based on this situation, in this chapter the authors have analysed the mental health of people affected due to COVID-19 by analyzing two parameters of mental health, boredom and stress, from social media posts by detecting different emotions and feelings expressed in the form of text. The authors have utilized the BERT pre-trained model on preprocessed data to create classification models of boredom, stress, and consequently, determining the emotion of the person. These models are used to determine the emotions (i.e., stress and boredom) during different stages of the COVID-19 pandemic.