2010 Volume 20 Issue 2 Pages 135-140
Similar to the research trends within various artistic realms, such as art, iterature, music, movies, and animation, in recent years, fiction studies are increasingly employing more sophisticated techniques of computational analysis. The aims of the present study are to quantitatively analyze the surface vocabulary of a literary text into the minimum components that reflect the writer's characteristic style and to identify style transitions. The target data consists of the full-length works of Haruki Murakami, as a representative of modern Japanese literature. The works are grouped in terms of writing styles through a clustering analysis of the textual vocabulary which was initially classified according to both word class and semantic categories. While the analysis results based on word-class categories yielded cluster that reflect a diachronic division, such as an "early trilogy", the results based on semantic categories yielded a cluster for the "Nezumi Tetrabiblos" that adds another work which is referred to as a sequel to the "early trilogy".