Mapping the digital footprints of science teachers in China. A YouTube network analysis

Abstract

This study examines the social media networks of science teachers in China on YouTube through the application of NodeXL-based social network analysis. By identifying key structural patterns and interaction dynamics, the research aims to reveal how science teachers engage, communicate, and develop professionally within social media environments. Using a mixed-methods approach that integrates quantitative network metrics with qualitative content analysis, the study explores information diffusion processes and thematic trends among Chinese science educators on YouTube. The findings indicate significant regional disparities in China’s science education infrastructure, persistent biases in international media portrayals of experimental science conditions in China, and strong public interest in qualification requirements for foreign science teachers working in the country, which emerged as the most prominent discussion topic. Through visual network mapping, this study illustrates the embedded positions of science teachers within YouTube-based social networks and provides insights into their professional development trajectories, school and employment environments, and approaches to science curriculum implementation. Overall, this research offers a novel social media–based perspective for understanding the dynamics of science teachers in China and contributes methodological value to studies of teacher development and educational quality in the digital era.