ChatGPT and International Chinese Language Education: A Bibliometric and Content Analysis Based on CiteSpace

The emergence of generative artificial intelligence, represented by ChatGPT, has created new opportunities for the development of International Chinese Language Education (ICLE), while simultaneously posing significant challenges to traditional teaching models, teacher roles, and learning assessment systems. Over the past two years, Chinese scholars have conducted multidimensional research on the application value, potential risks, and response strategies of ChatGPT in ICLE, producing a body of representative academic fruit. Taking 17 relevant studies published in China over the past two years as the research corpus, this study integrates qualitative content analysis with bibliometric analysis using CiteSpace to systematically examine the thematic structure, research hotspots, and developmental trends of ChatGPT-related ICLE research. The findings indicate that existing studies mainly focus on pedagogical applications, teacher role transformation, educational technology ethics, and language quality assessment. Overall, the field demonstrates a developmental trajectory from macro-level discussions toward more concrete pedagogical and empirical investigations. However, limitations remain in terms of empirical depth, theoretical integration, and the construction of evaluation frameworks. Based on these findings, this paper proposes directions for future research, aiming to provide references for the high-quality development of ICLE in the context of generative artificial intelligence.