It can be considered verso form of style-based document authentication (Echtheitskritik), which has valuable applications that extend well beyond the domain of literary analysis, preciso, for instance, the domain of forensic sciences. According preciso Stamatatos’s 2009 survey of the field, ‘[t]he main preoccupazione behind statistically or computationally-supported authorship attribution is that by measuring some textual features we can distinguish between texts written by different authors.’22 22 Di nuovo. Stamatatos, ‘Verso survey’ (n. 14, above) 538. This basic assumption implies that it should be possible esatto assess, for any new unseen document, whether or not it was written by other authors for whom we have texts available. Nowadays computational authorship studies are often considered a subfield of stylometry mediante the digital humanities, the broader computational study of the writing style of texts.23 23 D. Holmes, ‘The evolution of stylometry sopra humanities scholarship’, LLC 13 (1998) 111–17.

While stylometry has verso rich history, dating back to at least the nineteenth century, it is clear that it received its most important impetus only durante the past two or three decades, stimulated by the rise of (personal) computing and the increased availability of large bodies of text durante electronic form. Apart from the influential, yet more conventional, statistical analyses carried out by pioneers such as Mosteller and Wallace or John Burrows well before the 1990s, an influential approach sopra authorship studies has been to approach the attribution of anonymous texts as verso ‘text categorization’ problem.24 24 Mosteller and Wallace, Inference and disputed authorship (n. 4, above) and J. Burrows, Computation into criticism: per study of Jane Austen’s novels (Oxford 1987). Heavily influenced by parallel research mediante calcolatore elettronico science, the pensiero was preciso optimize per statistical classifier on example texts by a number of available candidate authors, much like a spam filter nowadays is still trained on manually annotated emails to learn how sicuro distinguish between ‘junk’ email and normal messages.25 25 F. Sebastiani, ‘Machine learning con automated text categorisation’, ACM Pc Surveys 34 (2002) 1–47. After allenamento such a classifier on this example scadenza, the classifier could then be used preciso categorize or classify anonymous text as belonging esatto one of the allenamento authors’ oeuvres.

It resembles a police lineup, mediante which the correct author of an anonymous text has to be singled out from per series of available candidate authors for whom reference or ‘training’ material is available

This text categorization setup is commonly known as ‘authorship attribution’.26 26 The following paragraph heavily draws on M. Koppel and Y. Winter, ‘Determining if two documents are written by the same author’, JASIST 65 (2014) 178–187. For a number of years, practitioners of stylometry have come esatto acknowledge the limitations of authorship attribution, because it necessarily assumes that the correct target author is indeed included per the servizio of candidates. Per many real-world cases, this problematic assumption cannot possibly be made, because the arnesi of relevant candidates is difficult or impossible preciso establish beforehand. Because of this, the setup of authorship verification has recently been introduced as per new framework: here, the task is onesto verify whether or not an anonymous document was written by one or several of verso series of candidate authors. Durante some sense, authorship verification redefines the text categorization problem by adding an additional category label: ‘None of the above.’

Mediante the present context, it should be emphasized that the problem posed by the HA is per ‘vanilla’ example of verso problem durante authorship verification: while the insieme indeed contains verso number of (auto-) attributions, the veracity of all of these has been questioned per previous scholarship

Verification is hence an increasingly common experimental setup in authorship studies, and is the topic of per dedicated track in the yearly PAN competition, an annual competition on finding computational solutions onesto issues sopra present-day textual forensics, mostly related to the detection of plagiarism, authorship, and affable software misuse (such as grooming or Wikipedia vandalism).27 27 The competition’s website is pan.webis.de. The most recent survey of an authorship verification track is: Di nuovo. Stamatatos et al., ‘Overview of the author identification task at PAN 2015′ con Working Notes Papers of the funziona raya CLEF 2015 Evaluation Labs, addirittura. L. Cappellato et al. (2015). Generally speaking, authorship verification is per more generic problem than authorship attribution – i.e. every attribution problem could, durante principle, be cast as per verification problem – but it has also proven esatto be more challenging. Durante our experiments, we have therefore attempted to radically minimize any assumptions on our part as puro the authorial provenance of the texts durante the HA. For each piece of text analysed below, we propose puro independently assess the probability that it was written by one of the (alleged) individual authors identified con the insieme.