Keyword Network Analysis of Discussions on International Students in South Korea

Objectives This study examines the main discussions related to international students in South Korea through keyword network analysis of text data from web news and academic papers produced in the last 3 years. Methods Keyword frequency, keyword centrality, topic modelling and ego network analysis were conducted to examine 1) main keywords and importance of main keywords, 2) subtopics of the texts, and 3) the characteristcs of the network of main keywords, by analysing 8,779 web documents and 856 academic papers. Textom and Netminer programs were used for data collection and analysis. Results As a result, in the web texts, ‘university’, ‘education’, ‘employment’, ‘inducement’, and ‘student’ were found to be the top frequent keywords while in the academic paper texts, ‘education’, ‘learning’, ‘Korean’, ‘culture’, and ‘university’ ranked among top frequent words. Topic modeling analysis showed that ‘university’ and ‘culture’ were common topics in both texts, and discussions related to ‘inducement’, ‘employment’, ‘learning’, and ‘culture’ were also subtopics of texts. Analysis of ego networks showed that ‘region’ had a major influence on forming networks of ‘university’ and ‘education’, and the keyword ‘employment’ and ‘inducement’ had a strong influence on the formation of its ego network each other. Conclusions It was found that ‘university’ was a key player in attracting and educating international students and ‘local community’ was actively involved in the related discussions. It was also found that inducing international students has been being carried out in connection with employment as a government effort to solve the social problem of Korea's low birth rate and aging population. Suggestions for building the cooperating system among the government, university and local community are discussed for attracting and settling international student talents.