  Online Social media (OSM) has become a primary platform for discussion on
diverse topics. Even famous and public figures often express their views on
various topics through OSM platforms. Novel Coronavirus officially called
COVID-19, which has become a pandemic and has created a crisis in human
history, is one such topic that has attracted a lot of attention on Twitter in
recent times. In this work, we analyze 29 million tweets spanning across three
months, to study highly influential users, which we called as leaders. We
identify these leaders using social network analysis and analyze their tweets
using text analysis techniques. We group these leaders in four clusters, namely
research, news, health and politics. Our analysis shows that i) all clusters
show a similar amount of fear in their tweets, ii) researchers and news cluster
display more sadness compared to others and, iii) health organizations and
politicians try to gain public trust. The text analysis shows that the
researchers are more concerned about understanding symptoms and developing
vaccination; news and politicians are mainly discussing about travel and
hygiene; and health organizations focuses on hygiene. Our descriptive analysis
helps us to extract various features that we used to classify tweets among the
four clusters with an accuracy of 96% AUC ROC.
