Characteristics of Post-pandemic International Chinese Language Learning: Insights from X-Data
DOI: https://doi.org/10.62517/jnme.202410305
Author(s)
Yanyan Li1, *, Wenhui Sun2
Affiliation(s)
1School of Literature and Journalism, Yantai University, Yantai, Shandong, China
2School of Mathematical Sciences, Soochow University, Suzhou, Jiangsu, China
*Corresponding Author.
Abstract
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.
Keywords
X-data; International Chinese Education; Online Learning; Sentiment Analysis; Topic Modeling
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