This research proposes a novel machine-learning approach to identify and categorize help-seeking tweets. We classify the tweets as ‘seeking oxygen’, ‘seeking medicines’, ‘seeking blood’, and ‘seeking ICU beds’, the four main help-seeking categories that we found in our new COVID-19 related tweets dataset. We show that this help-seeking data correlates well with the number of deaths in a region. We also estimate which of the four help-seeking categories are more strongly associated with deaths. Moreover, we relate the number of help-seeking tweets with the number of active COVID cases and the presence of medical infrastructure in the region. Using a new geo-coded Tweets dataset, we present the results for the ongoing pandemic in India, where medical shortages are being widely reported. We hope that using user-generated help-seeking content would allow Government and healthcare agencies to understand the unmet patient needs better and help them plan for the next wave.
Sumeet Kumar is an Assistant Professor of Information Systems at the Indian School of Business (ISB). He studies problems at the intersection of technology and society. He is interested in analysing user behaviour, quantifying polarisation on online forums , and finding advertisements disguised as regular content on online platforms. His current focus is on identifying implicit or hidden advertisements in videos posted on children’s platforms such as YouTube Kids.
Additionally, Professor Kumar has conducted research in software design and development, with particular emphasis on user experience. He has investigated the use of mobile phone sensors during emergencies to improve situational awareness. His study on the Wireless Emergency Alerts (WEA) service in the United States addressed several issues of critical importance to emergency alerts effectiveness and adoption. Notably, some of his research recommendations was included in the US Federal Communications Commission (FCC) proposed changes to WEA.
He completed his undergraduate education at Indian Institute of Technology (IIT) Kanpur. He holds two Master’s degrees—in Software Engineering and in Machine Learning--both from Carnegie Mellon University, where he also earned his doctorate degree.
