Nowadays, the coronavirus infection COVID-19 caused by the SARS-CoV-2 virus is a global concern as it leads to a dramatic increase in new infections and deaths among the population. Obviously, COVID-19 is not the first pandemic in the world. Doctors and researchers have seriously tackled various viruses such as Ebola, Mers-Cov, SARS, etc. Since the first headline about the coronavirus disease outbreak was published in December 2019, social networks have become a favourable ground for the spread of information about new COVID-19. And the impact of social media during such an unprecedented pandemic crisis is to be defined in this study. The author believes many outbreaks and pandemics could have been controlled promptly if experts had considered the social media data. In the current paper a social media platform Twitter was subjected to thorough analysis as it has the most accessible data sources currently available. Moreover, people in this social media are free to discuss and share their opinions about events in their daily life or express emotions associated with the pandemic. Thus, in the current study social data serves as the basis for analyzing the opinions and emotional attitude (sentiment) of the author of the text to some objects, processes or events. The aim of the research lies within the field of word processing in natural language. The automated sentiment analysis of messages from Twitter was carried out on the basis of modern computer systems and platforms. The large-scale identification of human emotions in social media is essential for international public influence, business decisions and policy development.