It can be considered per form of style-based document authentication (Echtheitskritik), which has valuable applications that extend well beyond the domain of literary analysis, onesto, for instance, the domain of forensic sciences. According preciso Stamatatos’s 2009 survey of the field, ‘[t]he main idea 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 Ed. Stamatatos, ‘A survey’ (n. 14, above) 538. This basic assumption implies that it should be possible sicuro 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 verso subfield of stylometry in the digital humanities, the broader computational study of the writing style of texts.23 23 D. Holmes, ‘The evolution of stylometry durante humanities scholarship’, LLC 13 (1998) 111–17.

While stylometry has per rich history, dating back esatto 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 per 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 in authorship studies has been esatto 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: a study of Jane Austen’s novels (Oxford 1987). Heavily influenced by parallel research sopra cervello elettronico science, the pensiero was esatto optimize a statistical classifier on example texts by verso number of available candidate authors, much like a spam filter nowadays is still trained on manually annotated emails sicuro learn how to distinguish between ‘junk’ email and normal messages.25 25 F. Sebastiani, ‘Machine learning durante automated text categorisation’, ACM Pc Surveys 34 (2002) 1–47. After istruzione such verso classifier on this example momento, the classifier could then be used puro categorize or classify anonymous text as belonging sicuro one of the preparazione authors’ oeuvres.

It resembles per police lineup, per which the correct author of an anonymous text has preciso 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 per number of years, practitioners of stylometry have quale sicuro acknowledge the limitations of authorship attribution, because it necessarily assumes that the correct target author is indeed included con the attrezzi of candidates. Con many real-world cases, this problematic assumption cannot possibly be made, because the serie of relevant candidates is difficult or impossible esatto establish beforehand. Because of this, the setup of authorship verification has recently been introduced as a new framework: here, the task is sicuro verify whether or not an anonymous document was written by one or several of verso series of candidate authors. Per some sense, authorship verification redefines the text categorization problem by adding an additional category label: ‘None of the above.’

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

Verification is hence an increasingly common experimental setup mediante authorship studies, and is the topic of a dedicated track in the yearly PAN competition, an annual competition on finding computational solutions sicuro issues durante present-day textual forensics, mostly related preciso the detection of plagiarism, authorship, and communautaire 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′ in Working Libretto Papers of the CLEF 2015 Evaluation Labs, e. L recensioni dating4disabled. Cappellato et al. (2015). Generally speaking, authorship verification is verso more generic problem than authorship attribution – i.ancora. every attribution problem could, con principle, be cast as verso verification problem – but it has also proven preciso be more challenging. Per our experiments, we have therefore attempted puro radically minimize any assumptions on our part as onesto the authorial provenance of the texts sopra the HA. For each piece of text analysed below, we propose to independently assess the probability that it was written by one of the (alleged) individual authors identified con the campione.