Abstract
In this study, we applied a machine learning method to model the sentence-final expressions in modern Japanese novels, and examined what kind of items exhibit remarkable fluctuations. Our experiments were conducted on a diachronic corpus consisting of contemporary novels published from 1910 to 2014. Sentence-final expression data were extracted from the corpus and used for analysis. First, we investigated changes in the diversity of sentence-final expressions using the index of vocabulary richness. Then, we constructed modeling related to sentence-final expressions, and extracted the instrumental items playing important roles in model construction. The results showed that the sentence-final expressions became more diverse with time. Furthermore, statistical modeling revealed characteristic tendencies suggesting changes in the narrative methods and techniques of novels.
https://ror.org/01fxdkm29 
