Analyzing the attitude of Indian citizens during the second wave of COVID-19: A text analytics study

BACKGROUND AND AIMS: The COVID-19 pandemic outbreak has created severe public health crises and economic consequences across the globe. This study used text analytics techniques to investigate the key concerns of Indian citizens raised in social media during the second wave of COVID-19. METHODS: In this study, we performed a sentiment and emotion analysis of tweets to understand the attitude of Indian citizens during the second wave of COVID-19. Moreover, we performed topic modeling to understand the significant issues and concerns related to COVID-19. RESULTS: Our results show that most social media posts were in neutral tone, and the percentage of posts that showed positive sentiment was less. Furthermore, emotion analysis results show that ‘Fear’ and ‘Surprise’ were the prominent emotions expressed by the citizens. Topic modeling results reveal that ‘High crowd’ and ‘political rallies’ are the two primary topics of concern raised by Indian citizens during the second wave of COVID-19. CONCLUSIONS: Hence, Indian government agencies should communicate crisis information and combating strategies to citizens more effectively in order to minimize the fear and anxiety amongst the public.