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Statistical Models for Authorship Attribution

  • Iryna Khomytska
  • Vasyl TeslyukEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1080)

Abstract

A combination of three hypothesis methods has been proposed for authorship attribution. These are: the Student’s t-test, the Kolmogorov-Smirnov’s test and the chi-square test. This combination of methods can perfect adequacy of authorship attribution. With the help of these methods, the quantity of phoneme groups is minimized. The texts can be differentiated by one or three phoneme groups. The minimization of phoneme groups facilitates authorship attribution. On the basis of the results obtained, statistical models have been built. The models show author-differentiating capability of phoneme groups in authorship attribution. This way the highest author-differentiating capability of phoneme groups is determined. New software realizes the models applied. The program makes transforming a text into transcription faster. The transcription variants of words available in the program are used.

Keywords

Statistical methods Minimization of phoneme groups Author-differentiating capability Authorship attribution 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Lviv Polytechnic National UniversityLvivUkraine

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