Idiolect:: An R package for forensic authorship analysis

Andrea Nini

Idiolect: An R package for forensic authorship analysis

Linguistics and English Language (L5)

Research output: Non-textual form › Software

Abstract

Carry out comparative authorship analysis of disputed and undisputed texts within the Likelihood Ratio Framework for expressing evidence in forensic science. This package contains implementations of well-known algorithms for comparative authorship analysis, such as Smith and Aldridge's (2011) Cosine Delta <doi:10.1080/09296174.2011.533591> or Koppel and Winter's (2014) Impostors Method <doi:10.1002/asi.22954>, as well as functions to measure their performance and to calibrate their outputs into Log-Likelihood Ratios.

Original language	English
Publisher	CRAN (Comprehensive R Archive Network)
Media of output	Online
Publication status	Published - 28 Aug 2024

Access to Document

https://doi.org/10.32614/CRAN.package.idiolectLicence: GNU GPL

Cite this

@misc{6f6b3254d2334eb9ae72ff46407b75e4,

title = "Idiolect:: An R package for forensic authorship analysis",

abstract = "Carry out comparative authorship analysis of disputed and undisputed texts within the Likelihood Ratio Framework for expressing evidence in forensic science. This package contains implementations of well-known algorithms for comparative authorship analysis, such as Smith and Aldridge's (2011) Cosine Delta or Koppel and Winter's (2014) Impostors Method , as well as functions to measure their performance and to calibrate their outputs into Log-Likelihood Ratios.",

author = "Andrea Nini",

year = "2024",

month = aug,

day = "28",

language = "English",

publisher = "CRAN (Comprehensive R Archive Network)",

address = "United States",

}

TY - ADVS

T1 - Idiolect:

T2 - An R package for forensic authorship analysis

A2 - Nini, Andrea

PY - 2024/8/28

Y1 - 2024/8/28

N2 - Carry out comparative authorship analysis of disputed and undisputed texts within the Likelihood Ratio Framework for expressing evidence in forensic science. This package contains implementations of well-known algorithms for comparative authorship analysis, such as Smith and Aldridge's (2011) Cosine Delta or Koppel and Winter's (2014) Impostors Method , as well as functions to measure their performance and to calibrate their outputs into Log-Likelihood Ratios.

AB - Carry out comparative authorship analysis of disputed and undisputed texts within the Likelihood Ratio Framework for expressing evidence in forensic science. This package contains implementations of well-known algorithms for comparative authorship analysis, such as Smith and Aldridge's (2011) Cosine Delta or Koppel and Winter's (2014) Impostors Method , as well as functions to measure their performance and to calibrate their outputs into Log-Likelihood Ratios.

UR - https://andreanini.github.io/idiolect/articles/idiolect.html

M3 - Software

PB - CRAN (Comprehensive R Archive Network)

ER -

Idiolect: An R package for forensic authorship analysis

Abstract

Access to Document

Other files and links

Fingerprint

Examining an author’s individual grammar

A Theory of Linguistic Individuality for Authorship Analysis

Attributing the Bixby Letter using n-gram tracing

Forensic linguistic authorship analysis of disputed texts

Interpretable cognitive linguistic authorship analysis using the Likelihood Ratio framework

The use of the likelihood ratio in forensic authorship analysis cases

Small language models for human-interpretable authorship analysis

Cite this

Idiolect: An R package for forensic authorship analysis

Abstract

Access to Document

Other files and links

Fingerprint

Research output

Examining an author’s individual grammar

A Theory of Linguistic Individuality for Authorship Analysis

Attributing the Bixby Letter using n-gram tracing

Impacts

Forensic linguistic authorship analysis of disputed texts

Activities

Interpretable cognitive linguistic authorship analysis using the Likelihood Ratio framework

The use of the likelihood ratio in forensic authorship analysis cases

Small language models for human-interpretable authorship analysis

Cite this