Characteristics of Post-pandemic International Chinese Language Learning: Insights from X-Data

This study uses sentiment analysis and topic modeling to analyze X-data on Chinese language learning both before and after the pandemic. Our analysis reveals shifts in sentiment and topics, as well as their underlying causes. We observe a notable increase in online learning as the primary mode of international Chinese language learning, accompanied by an escalated demand for high quality online learning resources. There is also a discernible polarization of learning sentiments in the post-pandemic era. In addition, the former emphasis on cultural exchange in language learning has shifted to economic and trade interactions, highlighting the commercial facets of international Chinese education.