Research Trends in Korean Comics and Webtoons Utilizing Text Mining

This study analyzes the changes in research trends by examining academic papers related to Korean comics and webtoons from 2000 to 2024 using text mining techniques. The data was divided into two periods: 2000-2015 and 2016 -2024, and analyses such as keyword frequency analysis, TF-IDF analysis, N-gram analysis, network centrality analysis, and CONCOR analysis were conducted. The analysis revealed that from 2000 to 2015, research primarily focused on “comics,” with initial studies on published comics and digital transformation. Keywords like “character,” “animation,” and “media” were prominent. From 2016 to 2024, “webtoons” emerged as a major research subject, with a shift towards digital platforms and narrative structures, highlighting keywords such as “narrative,” “storytelling,” and “reader experience.” The findings indicate that webtoons have established themselves as research subjects with academic, industrial, and educational value beyond being popular cultural content. They show significant potential, especially in areas like IP-based value creation, global market expansion, and storytelling-based learning. However, this study is limited to domestic papers and does not reflect global trends. Additionally, the focus on quantitative analysis leaves a gap in qualitative approaches. Future research should strengthen both domestic and international comparisons, incorporate qualitative approaches, and utilize industry data to propose the future of the digital content industry.