Art Stylometry: Recognizing Regional Differences in Great Works of Art

A review on authorship attribution in text mining

“…Although authorship attribution began with the stylistic analyses of humanities scholars (i.e., stylometry), with the advent of digital computers, the related techniques have been applied in music (e.g., musical style recognition and disputed musical authorship attribution; Brinkman et al, 2016; Tsai & Ji, 2020), art and painting (e.g., the identification of genuine paintings; Kokensparger, 2018; Yukimura et al, 2018), plagiarism detection (e.g., collaboration detection in documents; Gollub et al, 2013; AlSallal et al, 2019), spam detection (e.g., the detection of unsolicited and virus‐infested emails; Argamon et al, 2003; Rocha et al, 2017), and forensic investigation (e.g., author identification in anonymous or phishing emails; Gollub et al, 2013; Edwards, 2018). In the recent past, there has been increased research on code stylometry (Kokensparger, 2018; Kalgutkar et al, 2019; Quiring et al, 2019), which attempts to identify software authors from program source code using a feature analysis of programming styles. Its aims are to counter problems such as computer viruses and cyberattacks, as well as to detect unauthorized copying and plagiarism of software.…”