Corpus-based Study on the Changes of Key Words and Epidemic Situations of COVID-19 in Russian Media

This paper selected news report from Russian Media on COVID-19 since its outbreak in China (Jan. 9-March 16, 2020) and constructs a small-scale corpus. Based on the corpus, it conducts a research from two perspectives. First, corpus data are divided into 3 periods that consist of 9 stages, and the data are extracted with Python in terms of data information contribution. In each stage, 50 key words and their semantic fields are summarized and are also testified with real data from the corpus via critical corpus analysis. Via these steps the theme change of Russian news report of COVID-19 in China is handled. Second, word clouds via software Wordless explore the consistency of news focus of Russian media during Jan 9-March 16, 2020. It concludes that: the change of key words in Russian news report on COVID-19 in China has experienced three stages, with each one supporting China against the pandemic. Meanwhile, such news report in each stage(period) is closely related with other major events. Description and influence of COVID-19 in China on Russian economy have been the constant topic in Russian news report. This research has implications for the corpus-based research on Russian discourse and Russian social attitudes and ideology during the outbreak of COVID-19 in China.