employee from 01.01.2023 until now
FSFEI HE SSMU of the Ministry of Health of Russia (Department for International Development, Head)
employee from 01.01.2016 until now
Tomsk, Tomsk, Russian Federation
UDC 80
CSCSTI 16.31
CSCSTI 16.21
Russian Classification of Professions by Education 45.06.01
Russian Library and Bibliographic Classification 80
Russian Library and Bibliographic Classification 81
Russian Trade and Bibliographic Classification 84
Russian Trade and Bibliographic Classification 841
BISAK LAN000000 General
The authors applied the method of social network analysis to official and business medical discourse during the COVID-19 pandemic to examine the risk communication strategies. The corpus comprised news published on the official websites of the Russian Ministry of Health and the Federal Service for Consumer Protection and Welfare (Rospotrebnadzor) during the initial phase of restrictive measures in March 2020. The collected data underwent both mathematical processing and discourse analysis. The method of applied network analysis facilitated the visualization and interpretation of lexical representation of the pandemic in the professional news media discourse. The study utilized R Studio 4.4.1 and the Quanteda library with built-in base packages and the gsub function that replaces sections of lines. The topfeatures function revealed 30,723 most frequent lexical units. Findings indicate that medical news discourse predominantly adopted minimal to moderate communication strategies to mitigate public panic.
media discourse, risk communication, applied network analysis, news, natural language processing, lexical representation, COVID-19
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