「통일교육 지원법」상 대학에서의 통일교육 활성화를 위한 대학생 통일 인식 연구

In this study, I attempted to conduct a text network analysis of college students' perceptions of reunification in order to promote reunification education at universities, in accordance with the "Unification Education Support Act" using articles from the student newspaper at Soongsil University, which were searched for the keywords unification, North Korea, division, and North and South. The articles were divided into the Park government period and the Moon government period. Specifically, I utilized Topic Modeling, Degree Centrality, and Ego Network analysis, using NetMiner as the analysis program. Topic Modeling categorizes the target text group into the most revealing topics. Degree Centrality analysis extracts and analyzes words that have influence throughout the entire text, while Ego Network analysis analyzes individual connections between key words in the given text. The analysis results showed no significant differences in the results of Topic modeling, Degree Centrality, and Ego Network analysis between the Park and the Moon government periods. In Degree Centrality, words such as Soongsil, Unification, University, and North Korea appeared the same as nodes with strong connection centrality. The perception of reunification among college students, as expressed through the student newspaper, was shown to be influenced by the university's reunification-related education, courses, research, and training, rather than the government's orientation or current issues. These points should be considered for the long-term promotion of reunification education at universities.