Forensic Stylistics

Mcmenamin, Gerald

doi:10.1201/9781420041170.ch9

Cited by 44 publications

(41 citation statements)

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“…But recent developments of improved statistical techniques in conjunction with the wider availability of computer-accessible corpora have made the automatic and objective inference of authorship a practical option. This field has seen an explosion of scholarship, including several detailed book-length treatments [39,41,44,83,98,103,105,111,112,150]. Papers on authorship attribution routinely appear at conference ranging from linguistics and literature through machine learning and computation, to law and forensics.…”

Section: Structure Of the Review 235mentioning

confidence: 99%

Authorship Attribution

Juola

2007

FNT in Information Retrieval

468

232

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Authorship attribution, the science of inferring characteristics of the author from the characteristics of documents written by that author, is a problem with a long history and a wide range of application. Recent work in "non-traditional" authorship attribution demonstrates the practicality of automatically analyzing documents based on authorial style, but the state of the art is confusing. Analyses are difficult to apply, little is known about type or rate of errors, and few "best practices" are available. In part because of this confusion, the field has perhaps had less uptake and general acceptance than is its due.This review surveys the history and present state of the discipline, presenting some comparative results when available. It shows, first, that the discipline is quite successful, even in difficult cases involving small documents in unfamiliar and less studied languages; it further analyzes the types of analysis and features used and tries to determine characteristics of well-performing systems, finally formulating these in a set of recommendations for best practices.

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Section: Structure Of the Review 235mentioning

confidence: 99%

Authorship Attribution

Juola

2007

FNT in Information Retrieval

468

232

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“…“ Style is the variable element of human behaviour” [14]. Typical human activities carry invariant similarities.…”

Section: Introductionmentioning

confidence: 99%

“…They are different ‘correct’ ways of expressing the same thing, or they can be deviations from a norm such as mistakes, or idiosyncratic behaviours of the writers. McMenamin [14] offers an example to describe grammatically correct variations within the norm: if the norm is “I am going now”, a variation within the norm could be “I’m going now”, and a deviation could be “I be goin’ now”.…”

Section: Introductionmentioning

confidence: 99%

Network motifs for translator stylometry identification

2019

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Despite the extensive literature investigating stylometry analysis in authorship attribution research, translator stylometry is an understudied research area. The identification of translator stylometry contributes to many fields including education, intellectual property rights and forensic linguistics. In a two stage process, this paper first evaluates the use of existing lexical measures for the translator stylometry problem. Similar to previous research we found that using vocabulary richness in its traditional form as it has been used in the literature could not identify translator stylometry. This encouraged us to design an approach with the aim of identifying the distinctive patterns of a translator by employing network-motifs. Networks motifs are small sub-graphs which aim at capturing the local structure of a complex network. The proposed approach achieved an average accuracy of 83% in three-way classification. These results demonstrate that classic tools based on lexical features can be used for identifying translator stylometry if they get augmented with appropriate non-parametric scaling. Moreover, the use of complex network analysis and network motifs mining provided made it possible to design features that can solve translator stylometry analysis problems.

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“…Writer identification has a long history, perhaps dating to the origins of handwriting itself. For example, many textbooks and research papers have been published that describe the methodologies employed by forensic document examiners [4][5][6][7].…”

Section: Related Workmentioning

confidence: 99%

Text‐Dependent Writer Identification for Arabic Handwriting

Al-Maadeed

2012

Journal of Electrical and Computer Engineering

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This paper proposes a system for text-dependent writer identification based on Arabic handwriting. First, a database of words was assembled and used as a test base. Next, features vectors were extracted from writers' word images. Prior to the feature extraction process, normalization operations were applied to the word or text line under analysis. In this work, we studied the feature extraction and recognition operations of Arabic text on the identification rate of writers. Because there is no well-known database containing Arabic handwritten words for researchers to test, we have built a new database of offline Arabic handwriting text to be used by the writer identification research community. The database of Arabic handwritten words collected from 100 writers is intended to provide training and testing sets for Arabic writer identification research. We evaluated the performance of edge-based directional probability distributions as features, among other characteristics, in Arabic writer identification. Results suggest that longer Arabic words and phrases have higher impact on writer identification.

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Forensic Stylistics

Cited by 44 publications

References 1 publication

Authorship Attribution

Authorship Attribution

Network motifs for translator stylometry identification

Text‐Dependent Writer Identification for Arabic Handwriting

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