A Cross-Cultural Analysis of Sentiment in “COVID-19” Reportage of CCTV News and The New York Times

Yiyan TAN, Wenhui YANG, Yiran WANG, Xinye LI


Drawing support from the artificial intelligence platform of Baidu Cloud and the natural language processing approach, this paper provides an empirically-grounded micro-analysis of Sino-American news discourses on “COVID-19” pandemic in China 2020 by using keyword wordcloud analysis on sentiment expressions, namely the discourses from the websites of CCTV News and The New York Times. The authors analyzed the media’s intended attitudes expressed with sentiment, and found that the attitude of the Chinese people and China’s media towards the epidemic was mostly positive; while New York Times was mostly negative about the epidemic, especially at the peak of the outbreak. Such a difference presents a prevalent manifestation of recognition towards the epidemic led by either government or media institutions while people face uncertainties caused by corona virus, which may further influence the public opinion and attitudes towards the epidemic, which in turn has broader social/political-interactional purposes and public cognitive construction.



Sino-American news reports; COVID-19 pandemic; Epidemic; Attitude; Sentiment expressions

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DOI: http://dx.doi.org/10.3968/12849


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