Abstract
One of the most significant and rapidly developing fields of data analysis is information flow management. In the course of the analysis targeted and stochastic dissemination patterns are studied. The solving of such problems is daunting due to the global growth of the amount of information and its availability for a wide range of users. The paper presents a study of dissemination of information in open networks on the example of COVID-19. The study was conducted with the use of web scraping, methods of linguistic analysis and visual analytics. As sources of information variety of sources were used, such as the largest world and Russian information services, social networks and instant messengers. The paper considers statistical analysis of English media articles and posts form Twitter, dissemination of data flows between countries and information source. The developed methods can be scaled up to analyse information events of various topics. © 2021 National Research Nuclear University. All rights reserved.
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