This study is the first to examine the impact of media credibility on the sustainable travel intention of Chinese residents in the post-pandemic context. Specifically, the mechanisms by which media credibility influenced the sustainable travel intentions of Chinese residents through risk perception are studied. This study developed an extended theory of planned behavior (TPB) model and used a structural equation model (SEM) to analyze the 1219 valid samples received from online questionnaires. The results revealed that media credibility has a negative impact on risk perception of COVID-19 in the post-pandemic context. This suggested that trusted media, messages, and information sources can reduce the risk perception of COVID-19 when individuals contemplate travel. Risk perception negatively affects subjective norms, attitudes, and perceived behavioral control, while these three variables positively influence sustainable travel intention. Significantly, subjective norms have a stronger impact on the sustainable travel intention of Chinese residents than the remaining variables, demonstrating that, in a collective society, an individual’s intention to travel is more susceptible to influence by government sanctions as well as the unsupported opinions of their family and friends. This study makes up for the lack of focus on the media in sustainable tourism research and provides novel insights for future studies.

Large-scale, widespread COVID-19 vaccination is the most effective means of cutting off the spread of the novel coronavirus and establishing an immune barrier. Due to the large population base in China, it has been a very difficult task to establish such an immune barrier. Therefore, this study aims to explore the public’s discussions related to COVID-19 vaccinations on microblogs and to detect their sentiments toward COVID-19 vaccination so as to improve the vaccination rate in China. This study employed machine learning methods in the field of artificial intelligence to analyze mass data obtained from SinaWeibo. A total of 1,478,875 valid microblog texts were collected between December 2020 and June 2022, the results of which indicated that: (1) overall, negative texts (38.7%) slightly outweighed positive texts (36.1%); “Good” (63%) dominated positive texts, while “disgust” (44.6%) and “fear” (35.8%) dominated negative texts; (2) six overarching themes related to COVID-19 vaccination were identified: public trust in the Chinese government, changes in daily work and study, vaccine economy, international COVID-19 vaccination, the COVID-19 vaccine’s R&D, and COVID-19 vaccination for special groups. These themes and sentiments can clarify the public’s reactions to COVID-19 vaccination and help Chinese officials’ response to vaccine hesitancy. Furthermore, this study seeks to make up for the lack of focus on big data in public health and epidemiology research, and to provide novel insights for future studies.