Research Trends in the Chaos Theory of Careers Using Keyword Network Analysis and Topic Modeling

This study aimed to analyze research trends related to the Chaos Theory of Careers(CTC) by employing keyword network analysis and topic modeling. To this end, a total of 58 studies published in domestic and international journals from 2000 to 2024—which marks the beginning of scholarly attempts to apply chaos theory to the career domain—were selected for analysis. After examining the general characteristics of the selected studies, keyword network analysis and Latent Dirichlet Allocation(LDA) topic modeling were conducted using Python 3.12, following a thorough data preprocessing process. The findings revealed several trends in the research on the Chaos Theory of Careers. First, although studies on CTC have been continuously conducted since the year 2000, the volume of domestic research remains relatively low compared to international research, and the research methods have shown a tendency to rely heavily on literature reviews. Second, the results of the keyword network analysis indicated that the core concepts of the Chaos Theory of Careers ranked highly in terms of frequency, TF-IDF, and centrality measures. In contrast, keywords related to practical techniques, interventions, applications, or target groups appeared in mid-to-lower ranks. This suggests that most research on CTC to date has focused on conceptualization rather than empirical applications in career counseling or educational settings. Third, the topic modeling analysis identified four major thematic clusters in the body of research: (1) adult career development reflecting the uncertainty of the uncertain world of work, (2) CTC-based career counseling techniques, (3) CTC-oriented career education for university students’ career decision-making, and (4) the development of CTC-based career models. The study also analyzed how the influence of these topics varied across different time periods, thereby shedding light on recent research trends. These findings can be utilized as foundational data for diverse studies exploring the chaos theory of career, an alternative perspective, especially during periods of increasing uncertainty.