Stylochronometry: Timeline Prediction in Stylometric Analysis

Abstract

We examine stylochronometry, the question of measuring change in linguistic style over time within an authorial canon and in relation to change in language in general use over a contemporaneous period. We take the works of two prolific authors from the 19th/20th century, Henry James and Mark Twain, and identify variables that change for them over time. We present a method of analysis applying regression on linguistic variables in predicting a temporal variable. In order to identify individual authors’ effects on the model, we compare the model based on the novelists’ works to a model based on a 19th/20th century American English reference set. We evaluate using R2 and Root mean square error (RMSE), that indicates the average error on predicting the year. On the two-author data, we achieve an RMSE of 7.2 years on unseen data (baseline: 13.2); for the larger reference set, our model obtains an RMSE of 4 on unseen data (baseline: 17).