Earticle

초록

영어

As South Korea increasingly relies on foreign workers to address workforce shortages in its aging society, this study investigates occupational safety challenges foreign workers face, especially in labor-intensive industries. Despite their critical role in sectors such as manufacturing, foreign workers remain highly vulnerable to workplace hazards, primarily due to language barriers and cultural gaps that obstruct effective risk communication and safety instruction. Although multilingual policies have been introduced to address these limitations, they often fail to reflect the linguistic and cultural diversity of the foreign workforce. Existing research has underscored the necessity of culturally adaptive safety education; however, previous studies have predominantly relied on static survey data, limiting their responsiveness to rapidly evolving industrial risks. To bridge this gap, this study aims to analyze a substantial corpus of unstructured news articles related to industrial safety using text mining techniques and BERTopic-based modelling. This study identified seven key themes related to safety education. However, the current safety training were found to inadequately address the linguistic and cultural needs of foreign workers. Network analysis revealed structural links among policy, education, and integration, with foreign workers and safety education as central terms. The findings suggest the importance of developing safety training strategies that are culturally and linguistically responsive to the needs of foreign workers. By offering a data-driven exploration of overlooked safety issues, this study provides practical implications for improving occupational safety policy and fostering inclusive safety practices in South Korea’s high-risk industries.

목차

ABSTRACT
Ⅰ. Introduction
Ⅱ. Theoretical Background
2.1. Foreign Worker Safety Training
2.2. Risk communication
Ⅲ. Research Methods
3.1. Text Mining Techniques and BERT Topic Modeling
3.2. Data Collection and Pre-processing Process
Ⅳ. Research Results
4.1. Keyword Frequency Analysis Results
4.2. Topic Modeling Results
4.3. Network Analysis Results
Ⅴ. Discussion and Implications
5.1. Discussion
5.2. Academic and Practical Implications
5.3. Limitations of the Study and Future Research Directions
Acknowledgements

저자

• Ajin Pyo [ Ph.D. Candidate, Management Information Systems at Dongguk University, Korea ]
• Eunyoung Lee [ Assistant Professor, Department of Social Welfare at Dongguk University, Korea ]
• Sang-Hyeak Yoon [ Assistant Professor, Department of Management Information System, College of Business, Dongguk University, Korea ] Corresponding Author

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