APPLYING SOCIAL NETWORK ANALYSIS TO RISK COMMUNICATION IN THE PROFESSIONAL SEGMENT OF NEWS MEDIA DISCOURSE
Abstract and keywords
Abstract (English):
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.

Keywords:
media discourse, risk communication, applied network analysis, news, natural language processing, lexical representation, COVID-19
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References

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