Several researchers have presented several studies on the CoViD-19 outbreak like on the epidemiological aspects of the disease, diagnostics method of the novel coronavirus, clinical characteristics, transmission, and vaccines. However, the sentiments and behaviour of the people online particularly in twitter remain unexplored. In this paper we focused on exploring peoples’ tweets to uncover their attitudes, sentiments, and find out the network effects of peoples’ tweets and the heated topics. Text mining approach was utilized using sentiment and social network analysis. Term document matrix, word cloud, nrc_sentimentdictionary, histogram, community edge betweenness algorithm, and network graph were used in the study. An API account was created wherein15000 tweets were extracted from March 22, 2020 to March 31, 2020containing the keyword #COVID-19 to make a working data for analysis. Results from the social network analysis showed a close relationship between tweets where people are globally talking part by sharing information about the CoViD-19. The peoples’ attitude showed the willingness to follow government precautionary measures to lessen the impact of the virus. Despite of the fear and sadness felt by the people over twitter, sentiment analysis revealed positive emotion towards the crisis. Such insights are significant when guiding people to respond appropriately and helping them to learn to cope with the sudden infectious disease as it promotes social stability. This will also help the authorities understand the sentiments and anxieties of the people, giving a strong direction to enact policies beneficial to the people. Moreover, social network analysis can be used as a method of understanding the behaviour of the people online and how these people are talking towards an issue.