One of the most significant and rapidly developing works in the field of data analysis is information flow management. Within the analysis targeted and stochastic dissemination patterns are studied. The solving of such problems is relevant due to the global growth in the amount of information and its availability for a wide range of users. The paper presents a study of dissemination of information messages in open networks on the example of COVID-19. The study was conducted with the use of visual analytics. Informational messages from the largest world and Russian information services, social networks and instant messengers were used as sources of information. Due to the large amount of information on the topic, the authors proposed a pattern of the wave-like dissemination of information on the example of topic clusters on the connection of COVID-19, hydroxychloroquine and 5G. The developed methods can be scaled up to analyze information events of various topics.

graph analysis, geospatial analysis, Web-technology, COVID 19, data scrapping, misinformation

Ulizko Mikhail,  mulizko@kaf65.ru,  orcid.org/0000-0003-2608-8330,  Plekhanov Russian University of Economics; National Research Nuclear University MEPhI (Moscow Engineering Physics Institute)

Tretyakov Evheniy,  etreyakov@kaf65.ru,  orcid.org/0000-0002-1051-8562,  Plekhanov Russian University of Economics; National Research Nuclear University MEPhI (Moscow Engineering Physics Institute)

Tukumbetova Rufina,  rrtukumbetova@kaf65.ru,  orcid.org/0000-0002-1976-1390,  Plekhanov Russian University of Economics; National Research Nuclear University MEPhI (Moscow Engineering Physics Institute)

Artamonov Alexey,  aartamonov@kaf65.ru,  orcid.org/0000-0002-9140-5526,  Plekhanov Russian University of Economics; National Research Nuclear University MEPhI (Moscow Engineering Physics Institute)

Esaulov Mikhail,  mnesaulov@mephi.ru,  orcid.org/0000-0002-3062-8005,  National Research Nuclear University MEPhI (Moscow Engineering Physics Institute)