The Study of Japanese Web Novels Using Text Mining ：Focusing on ‘Shōsetsuka ni Narō’ and ‘Kakuyomu’

This study employs text mining to analyze and compare the distinctive characteristics and differentiation strategies of two major Japanese web novel platforms, “Shōsetsuka ni Narō” and “Kakuyomu,” using their metadata. Text mining was chosen as it efficiently processes large-scale data, making it an appropriate method to capture the extensive and varied characteristics of Japanese web novel platforms. This study specifically examines changes in annual submission counts, genre distribution, main terms within story summaries, and keyword frequency across both platforms to understand their distinctive trends and reader preferences in detail. The analysis reveals that “Shōsetsuka ni Narō” has established a broad collection centered on isekai fantasy, showing popularity in female-oriented works, which aligns with the preferences of a young reader demographic and places it at the heart of Japan’s web novel trends. In contrast, “Kakuyomu,” as a newer platform, differentiates itself by featuring exclusive “Kakuyomu Only” content and embracing niche genres like SF, mystery, and history, thereby appealing to a broader readership. Additionally, the two platforms’ differing age restriction policies and content management approaches offer readers a distinct experience. This study aims to outline the characteristics of these leading platforms within the Japanese web novel market and understand how their unique strategies impact reader engagement.