Indian Healthcare Infrastructure Analysis during COVID-19 using Twitter Sentiments

ABSTRACT

The COVID-19 pandemic has wreaked havoc on the worldwide economy. We employ semantic analysis to compare and assess the healthcare infrastructure of different Indian states with varying population and GDP levels. The goal is to (1) determine the relative lag in medical resources by state, (2) examine the states' responses to the COVID-19 economic crisis, and (3) recommend potential investments shortly based on the COVID-19 pandemic's findings. Our approach benefits from semantically analyzing tweets at the height of the most horrific second wave, which allows us to catch the tremors and quick shifts induced by wide-scale deaths. To approximate the infrastructure metrics, we leverage the social attitudes from Twitter data. The findings reveal that the lower expenditure on medical infrastructure is the primary challenge for the majority of the states in the country. Our research shows how data from state and city-specific Twitter posts may be utilized to comprehend local issues and opinions around healthcare leading to more directed and widely agreeable social media content-based rules. © 2022 IEEE.