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Proceedings Article

Advanced text authorship detection methods and their application to biblical texts

[+] Author Affiliations
Tālis Putniņš, Domenic J. Signoriello, Samant Jain, Matthew J. Berryman, Derek Abbott

Univ. of Adelaide (Australia)

Proc. SPIE 6039, Complex Systems, 60390J (January 13, 2006); doi:10.1117/12.639281
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From Conference Volume 6039

  • Complex Systems
  • Axel Bender
  • Brisbane, Australia | December 11, 2005

abstract

Authorship attribution has a range of applications in a growing number of fields such as forensic evidence, plagiarism detection, email filtering, and web information management. In this study, three attribution techniques are extended, tested on a corpus of English texts, and applied to a book in the New Testament of disputed authorship. The word recurrence interval based method compares standard deviations of the number of words between successive occurrences of a keyword both graphically and with chi-squared tests. The trigram Markov method compares the probabilities of the occurrence of words conditional on the preceding two words to determine the similarity between texts. The third method extracts stylometric measures such as the frequency of occurrence of function words and from these constructs text classification models using multiple discriminant analysis. The effectiveness of these techniques is compared. The accuracy of the results obtained by some of these extended methods is higher than many of the current state of the art approaches. Statistical evidence is presented about the authorship of the selected book from the New Testament.

© (2005) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
Citation

Tālis Putniņš ; Domenic J. Signoriello ; Samant Jain ; Matthew J. Berryman and Derek Abbott
"Advanced text authorship detection methods and their application to biblical texts", Proc. SPIE 6039, Complex Systems, 60390J (January 13, 2006); doi:10.1117/12.639281; http://dx.doi.org/10.1117/12.639281


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