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 19 th /20 th 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 19 th /20 th century American English reference set. We evaluate using R 2 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).

A data science and machine learning approach to continuous analysis of Shakespeare's plays

“…On the other hand, earlier Shakespeare plays also showed a different styles, such as the rhyming iambic pentameter used by Shakespeare in plays written in 1594-1595 [Harbage, 1962]. Stylistic and linguistic analysis such as the use of certain rare words, rhymes, and the use of colloquialism-in-verse were also used to determine the exact date of creation of Shakespeare's plays [Taylor, 1987;Whitworth, 2003], indicating that Shakespeare's style has changed over time [Klaussner and Vogel, 2015;Klaussner, 2018;Klaussner and Vogel, 2018;Andreev, 2019;Seminck et al, 2021Seminck et al, , 2022. While these elements are not necessarily related to sentiments and other elements tested in this study, they are in agreement with the contention that the plays of Shakespeare exhibited differences in their style in different years.…”