A Corpus-Based Critical Discourse Analysis of News Reports about China on COVID-19 in The New York Times

Abstract

In 2019, the COVID-19 has spread around the world and there have been numerous reports about this topic. In fact, these seemingly objective and unbiased news reports contain underlying ideologies and influence readers’ opinions and judgments. During April and July 2020, negative public perceptions of China in the U.S. reached a historical high point. Therefore, this study uses Fairclough’s three-dimensional analysis model as the theoretical framework and Halliday’s systemic-functional grammar as the analytical tool, and selects 40 articles from the beginning of April to the end of July 2020 as the research corpus with the help of AntConc 4.0.5 (macOS) 2022, combining qualitative and quantitative research methods. The following key findings emerged from the study. Firstly, The New York Times tends to use negative linguistic elements to portray an arbitrary image of China, but the expression of Sino-U.S. relations is neutral. Secondly, The New York Times tends to use direct quotations in its news coverage, but the quotations tend to be negative in content. Finally, political, economic and cultural aspects have a direct impact on the ideological production of news reports. This thesis contributes to the enrichment of research in the field of critical discourse analysis and enhances the critical awareness of readers.