Paper
13 January 2006 Advanced text authorship detection methods and their application to biblical texts
Tālis Putniņš, Domenic J. Signoriello, Samant Jain, Matthew J. Berryman, Derek Abbott
Author Affiliations +
Proceedings Volume 6039, Complex Systems; 60390J (2006) https://doi.org/10.1117/12.639281
Event: Microelectronics, MEMS, and Nanotechnology, 2005, Brisbane, Australia
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.
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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 (13 January 2006); https://doi.org/10.1117/12.639281
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Cited by 16 scholarly publications and 1 patent.
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KEYWORDS
Data modeling

Statistical analysis

Mahalanobis distance

Data mining

Artificial intelligence

Forensic science

Statistical modeling

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