Topic modeling and evolutionary trends of China’s language policy: A LDA-ARIMA approach

This study extracts 1,420 policy texts from official websites and outlines the following findings: (1) Language policies focus on maintaining a harmonious linguistic environment, addressing educational inequality, and protecting language resources. (2) Since 2014, most topics have exhibited fluctuating yet sustained growth trend, particularly in language education and research. (3) Except for language resources, the predicted values of the remaining six topics will show a growing trend from 2024 to 2028. Based on these findings, we propose policy recommendations such as strengthening language research, developing a multilingual education system, and optimizing language resource management.

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Publication Details

Journal
PLoS ONE
Published
2025-05-28
DOI
https://doi.org/10.1371/journal.pone.0324644
Citations
2
Primary Topic
Computational and Text Analysis Methods
Type
article
Field-Weighted Citation Impact
10.68

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article

Topic modeling and evolutionary trends of China’s language policy: A LDA-ARIMA approach

Tianxin Li, X. Ke, Hui Shi
2 citations
PLoS ONE
Computational and Text Analysis Methods
10.68
article

Topic modeling and evolutionary trends of China’s language policy: A LDA-ARIMA approach

Tianxin Li, X. Ke, Hui Shi
article en
2 citations

Abstract

This study extracts 1,420 policy texts from official websites and outlines the following findings: (1) Language policies focus on maintaining a harmonious linguistic environment, addressing educational inequality, and protecting language resources. (2) Since 2014, most topics have exhibited fluctuating yet sustained growth trend, particularly in language education and research. (3) Except for language resources, the predicted values of the remaining six topics will show a growing trend from 2024 to 2028. Based on these findings, we propose policy recommendations such as strengthening language research, developing a multilingual education system, and optimizing language resource management.

PLoS ONEVol. 20(5)
Nanjing Normal University (CN), Shaanxi Normal University (CN)
Social Science Foundation of Shaanxi Province
Quality Education
Openalex Percentile: Top 2%
Computational and Text Analysis Methods
10.68
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