Yang Zhang

Objective/Significance: To measure the international communication capacity of China’s English academic journal papers based on social media platforms. Method/Process: Social network analysis, content analysis and emotion analysis were used to describe the diffusion structure of China’s English academic journal papers on Twitter from the aspects of network structure and identify important node users, explore the identity characteristics and emotion characteristics of users as well as diffusion capability of journals of different disciplines. Conclusion/Discovery: Journal articles in the fields of natural sciences and engineering as well as humanities and social sciences exhibit a strong positive correlation between their diffusion structure and network size. Networks with a mixed diffusion structure typically have larger network sizes. The users occupying key positions in the diffusion network typically have profile information that is academically relevant. The retweets and comments are mainly statements without emotional inclination, and the comments are mainly summary descriptions of the papers. The distribution of diffusion width, diffusion strength and diffusion speed of each discipline is significantly different. There is a significant positive correlation between the diffusion structure of papers and their diffusion capabilities. Innovation/Value: To reveal the diffusion structure and characteristics of China’s English academic journal papers on social media platforms, so as to provide reference for expanding the visibility of China’s English academic journals and improving the international dissemination capacity of China’s English journals.

Debunking offers a promising approach to counteracting social media rumors during public health emergencies. However, the effective mechanisms of rumor debunking on social media remain unverified. This study employs an interpretable machine learning approach, combined with information and communication theories, to investigate social media rumor debunking effectiveness and its influencing factors. A total of 10,150 COVID-19 rumor-debunking posts and other relevant data on Sina Weibo were collected for analysis. The results showed that the beneficial impacts of debunking rumors surpass the adverse consequences and revealed significant differences in debunking effectiveness across diverse rumor types, topics, and involvement levels.