The Evolution of Stylometry in Humanities Scholarship

Computational methods in authorship attribution

“…Many studies since that of Mosteller and Wallace have shown the efficacy of function words for authorship attribution in different scenarios (Morton 1978;Burrows 1987;Karlgren & Cutting 1994;Merriam & Matthews 1994;Kessler et al 1997;Argamon et al 1998;Holmes 1998;de Vel et al 2001;Holmes et al 2001aHolmes et al , 2001bBaayen et al 2002;Binongo 2003;Juola & Baayen 2003;Zhao & Zobel 2005;Argamon & Levitan 2005;Koppel et al 2005Koppel et al , 2006a, confirming the hypothesis that different authors tend to have different characteristic patterns of function word use.…”

“…More recently, Graham et al (2005) and Zheng et al (2006) used neural networks on a wide variety of features. Other studies used k-nearest neighbor (Kjell et al 1995;Hoorn et al 1999;Zhao & Zobel 2005), Naive Bayes (Kjell 1994a;Hoorn et al 1999;Peng et al 2004), rule learners (Holmes & Forsyth 1995;Holmes 1998;Argamon et al 1998;Koppel & Schler 2003;Abbasi & Chen 2005;Zheng et al 2006), support vector machines (De Vel et al 2001;Diederich et al 2003;Koppel & Schler 2003, Abbasi & Chen 2005Koppel et al 2005;Zheng et al 2006), Winnow (Koppel et al 2002;Argamon et al 2003;Koppel et al 2006a), and Bayesian regression Madigan et al 2006;Argamon et al 2008). Further details regarding these studies can be found in the Appendix.…”

“…In this section, we consider a number of feature types that have been, or might be, used for the attribution problem. A number of earlier works that have surveyed and/or compared various types of feature sets include Forsyth & Holmes (1996), Holmes (1998), McEnery & Oakes (2000), Love (2002), Zheng et al (2006), Abbasi & Chen (2008) and Juola (2008). We note that in addition to the above-cited work dealing with attribution of texts in a variety of genres, there has also been a fair amount of work on attribution of programming code, music, art and other media; we regard that work as beyond the scope of this paper.…”

Tensor Space Models for Authorship Identification

“…This line of research is known as stylometry [13]. Several hundreds of stylometric features have been proposed attempting to find measures that are reliable and accurate under varying text-length, text types, and availability of text processing tools.…”

“…indicating many applications of this technology, including forensics (identifying the authors of harassing email messages), intelligence (attributing messages to known terrorists), etc. [1,23,8,33,35] One main issue in the research on authorship identification is the definition of appropriate textual features to quantify the stylistic properties of texts [13]. Many different measures have been proposed including simple ones such as word frequencies or character n-gram frequencies and more complex ones requiring some sort of syntactic or semantic analysis [35].…”