Abstract
The purpose of this study is to analyze writing aspects in 110 expressive writing results conducted in liberal arts at D University using text mining and semantic network analysis. To this end, 110 pieces were finally selected for analysis. The analysis target went through a text preprocessing process such as synonymy combination and elimination of non-terms, then extracted key words and analyzed the connection relationship through network analysis. As a result of the analysis of the frequency of keywords, 'thought', 'exercise', 'friend', 'people', and 'life' were emphasized, and as a result of the analysis of the language network, “Exercise-Health-Soccer-Military-Taekwondo-Confidence,” “Picture-Draw-Admission,” “Friends-Friendly -Thanks,” and “Music-Enjoy-Singing-Sharing” were the main cluster words. As a result of the study, the author's self-expressive writing as a university student appeared in ways of individual internal reflection, self-identity formation, self-healing, emotional expression, and self-consolation. Examining university students' expressive writing aspects in liberal arts is meaningful in that it can be an opportunity to identify the characteristics of university students with clear environmental changes, seek classes necessary for future liberal arts education, and further explore their individual lives.
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