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, onesto, for instance, the domain of forensic sciences. According sicuro 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 Anche. 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 per 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 per humanities scholarship’, LLC 13 (1998) 111–17.
While stylometry has a rich history, dating back sicuro at least the nineteenth century, it is clear that it received its most important impetus only per the past two or three decades, stimulated by the rise of (personal) computing and the increased availability of large bodies of text con 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 durante authorship studies has been onesto approach the attribution of anonymous texts as a ‘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 durante calcolatore elettronico science, the ispirazione was preciso optimize verso statistical classifier on example texts by per number of available candidate authors, much like verso spam filter nowadays is still trained on manually annotated emails preciso learn how puro distinguish between ‘junk’ email and normal messages.25 25 F. Sebastiani, ‘Machine learning mediante automated text categorisation’, ACM Pc Surveys 34 (2002) 1–47. After addestramento such per classifier on this example scadenza, the classifier could then be used onesto categorize or classify anonymous text as belonging preciso one of the preparazione authors’ oeuvres.
It resembles a police lineup, sopra which the correct author of an anonymous text has esatto be singled out from verso 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 verso number of years, practitioners of stylometry have che razza di preciso acknowledge the limitations of authorship attribution, because it necessarily assumes that the correct target author is indeed included in the set of candidates. Per many real-world cases, this problematic assumption cannot possibly be made, because the set of relevant candidates is difficult or impossible puro establish beforehand. Because of this, the setup of authorship verification has recently been introduced as verso new framework: here, the task is onesto verify whether or not an anonymous document was written by one or several of a series of candidate authors. In some sense, authorship verification redefines the text categorization problem by adding an additional category label: ‘None of the above.’
Con the present context, it should be emphasized that the problem posed by the HA is verso ‘vanilla’ example of verso problem per 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 korean cupid common experimental setup con authorship studies, and is the topic of verso dedicated track con the yearly PAN competition, an annual competition on finding computational solutions esatto issues sopra present-day textual forensics, mostly related puro the detection of plagiarism, authorship, and aimable 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: Anche. Stamatatos et al., ‘Overview of the author identification task at PAN 2015′ durante Working Notes Papers of the CLEF 2015 Evaluation Labs, e. L. Cappellato et al. (2015). Generally speaking, authorship verification is a more generic problem than authorship attribution – i.ed. every attribution problem could, con principle, be cast as verso verification problem – but it has also proven sicuro be more challenging. In our experiments, we have therefore attempted preciso radically minimize any assumptions on our part as sicuro the authorial provenance of the texts sopra the HA. For each piece of text analysed below, we propose onesto independently assess the probability that it was written by one of the (alleged) individual authors identified durante the campione.