Presented here is a study on the semantic analysis of mainstream media news related to the COVID-19 outbreak in China that occurred at the end of 2019. Examining the most frequently used keywords and their co-occurrences, researchers can infer a semantic network that represents the major frames used in a large amount of text. Frames are cognitive structures that people use to understand and communicate about issues. Through framing, media and individuals choose to highlight certain aspects of the crisis while downplaying other aspects. This study demonstrates that Chinese mainstream media users applied 12 frames, including basic information, vaccines, politics, economy, and war metaphors, to analyze the public health crisis related to the COVID-19 outbreak. The study also explores how the use of these frameworks changed in different stages of the COVID-19 pandemic, providing new perspectives and content for research on crisis and emergency risk communication. Methodologically, this study demonstrates the feasibility of identifying frames in Chinese media news through text mining and semantic network analysis. From a practical perspective, the findings provide valuable insights for public health professionals in understanding Chinese media perception and formulating crisis communication strategies for future public health emergencies.

  • This study is to investigate the text semantic analysis of mainstream media news related to the COVID-19 outbreak in China that occurred at the end of 2019.

  • Examining the most frequently used keywords and their co-occurrences, researchers can infer a semantic network that represents the major frames.

  • Frames are cognitive structures that people use to understand and communicate about issues.

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