Development of methods, models, and means for the author attribution of a text

Authorship Attribution Methods, Challenges, and Future Research Directions: A Comprehensive Survey

“…Also, three research groups [53][54][55] used the method of determination of functional style effect and authorial style effect (MFSASE) and the Method of Complex Analysis (MCA) with a combination of ranking and style distance determination methods to test the feasibility of the research on Byron's and Moore's poetry. They showed that utilizing a combination of complex analysis and the multifactor method of determining the degree of style along with the authorial factor improves the efficiency of style and authorship attribution [56,57]. The mean frequency of occurrence was considered a criterion of style differentiation, assuming that the frequency of occurrence of consonant phoneme groups follows normal Gaussian distribution.…”

A review on authorship attribution in text mining

“…Furthermore, by studying 16 native‐English authors, Deng and Allahverdyan (2016) showed that rank‐frequency relations for phonemes can be described by the Dirichlet distribution and demonstrated that these relations without the frequencies of specific phonemes are author dependent. Khomytska et al (2018) conducted experiments on eight groups of consonant phonemes (labial, front‐alveolar, mid‐alveolar, post‐alveolar, nasal, sonorous, slit, and closed) in English texts related to fiction, conversational, newspaper, and scientific styles. They found that an accuracy of 95% is ensured by a combination of statistical methods (hypotheses, ranking, and determining the distances between styles).…”