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, esatto, for instance, the domain of forensic sciences. According onesto Stamatatos’s 2009 survey of the field, ‘[t]he main pensiero 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 Addirittura. Stamatatos, ‘Verso 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 per the digital humanities, the broader computational study of the writing style of texts.23 23 D. Holmes, ‘The evolution of stylometry con humanities scholarship’, LLC 13 (1998) 111–17.
While stylometry has verso rich history, dating back preciso at least the nineteenth century, it is clear that it received its most important impetus only sopra the past two or three decades, stimulated by the rise of (personal) computing and the increased availability of large bodies of text mediante 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 to 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: a study of Jane Austen’s novels (Oxford 1987). Heavily influenced by parallel research mediante computer science, the idea was sicuro optimize per statistical classifier on example texts by verso number of available candidate authors, much https://datingranking.net/it/matchocean-review/ like a spam filter nowadays is still trained on manually annotated emails esatto learn how onesto distinguish between ‘junk’ email and normal messages.25 25 F. Sebastiani, ‘Machine learning per automated text categorisation’, ACM Computer Surveys 34 (2002) 1–47. After training such a classifier on this example giorno, the classifier could then be used puro categorize or classify anonymous text as belonging esatto one of the training authors’ oeuvres.
It resembles a police lineup, in 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 per number of years, practitioners of stylometry have che to acknowledge the limitations of authorship attribution, because it necessarily assumes that the correct target author is indeed included durante the serie of candidates. Mediante many real-world cases, this problematic assumption cannot possibly be made, because the attrezzi of relevant candidates is difficult or impossible to establish beforehand. Because of this, the setup of authorship verification has recently been introduced as a 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.’
In the present context, it should be emphasized that the problem posed by the HA is per ‘vanilla’ example of verso problem in authorship verification: while the insieme indeed contains verso number of (auto-) attributions, the veracity of all of these has been questioned in previous scholarship
Verification is hence an increasingly common experimental setup durante authorship studies, and is the topic of a dedicated track in the yearly PAN competition, an annual competition on finding computational solutions onesto issues mediante present-day textual forensics, mostly related to the detection of plagiarism, authorship, and agreable 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: Ed. Stamatatos et al., ‘Overview of the author identification task at PAN 2015′ per Working Notes Papers of the CLEF 2015 Evaluation Labs, e. L. Cappellato et al. (2015). Generally speaking, authorship verification is verso more generic problem than authorship attribution – i.ed. every attribution problem could, per principle, be cast as per verification problem – but it has also proven sicuro be more challenging. Durante our experiments, we have therefore attempted sicuro radically minimize any assumptions on our part as esatto the authorial provenance of the texts durante 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 per the insieme.