Detection of changes in literary writing style using N-grams as style markers and supervised machine learning.

ABSTRACT: The analysis of an author's writing style implies the characterization and identification of the style in terms of a set of features commonly called linguistic features. The analysis can be extrinsic, where the style of an author can be compared with other authors, or intrinsic, where the style of an author is identified through different stages of his life. Intrinsic analysis has been used, for example, to detect mental illness and the effects of aging. A key element of the analysis is the style markers used to model the author's writing patterns. The style markers should handle diachronic changes and be thematic independent. One of the most commonly used style marker in extrinsic style analysis is n-gram. In this paper, we present the evaluation of traditional n-grams (words and characte

SUBMITTER: Rios-Toledo G 

PROVIDER: S-EPMC9299308 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature