Synthesis of Quantitative Stylometry and Classic Linguistic Analysis: Expert Practice of Differentiation between Parody and Plagiarism in Translated Texts

Abstract

The article presents a comprehensive study of the stylistic features of J.K. Rowling’s “Harry Potter and the Philosopher’s Stone” and D. Emets’ “Tanya Grotter and the Magic Contrabass” texts using computational stylometry methods, machine learning and Classic linguistic analysis. The study aims to provide an objective assessment of stylistic similarity/difference degree between the texts in the context of the legal dispute over plagiarism and parody. The methodology of examination includes two complementary approaches: quantitative analysis using the Random Forest machine learning model, which allows extracting and evaluating stylistic features based on lexical, morphological, and syntactic text characteristics, and qualitative linguistic analysis focusing on phonetic study of proper names, morphological analysis of nomination structures and pragmatic interpretation of stylistic features. It is demonstrated that the texts by Rowling and Emets have significant stylistic differences identified both through machine learning and traditional linguistic analysis. The study contributes to the methodology of forensic linguistic and authorship examinations by showing the effectiveness of a comprehensive approach to differentiation between parody and plagiarism in the context of translated literature and parody works.