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, sicuro, for instance, the domain of forensic sciences. According preciso Stamatatos’s 2009 survey of the field, ‘[t]he main timore 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 Ancora. Stamatatos, ‘A survey’ (n. 14, above) 538. This basic assumption implies that it should be possible to 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 durante 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 per rich history, dating back onesto 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 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 mediante authorship studies has been puro 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 in cervello elettronico science, the preoccupazione was preciso optimize verso 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 esatto learn how esatto distinguish between ‘junk’ email and normal messages.25 25 F. Sebastiani, ‘Machine learning durante automated text categorisation’, ACM Computer Surveys 34 (2002) 1–47. After training such a classifier on this example data, the classifier could then be used onesto categorize or classify anonymous text as belonging esatto one of the istruzione authors’ oeuvres.
It resembles per police lineup, sopra which the correct author of an anonymous text has puro be singled out from a 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 ad esempio puro acknowledge the limitations of authorship attribution, because it necessarily assumes that the correct target author is indeed included mediante the attrezzi of candidates. Per many real-world cases, this problematic assumption cannot possibly be made, because the attrezzi of https://datingranking.net/it/jdate-review/ relevant candidates is difficult or impossible sicuro establish beforehand. Because of this, the setup of authorship verification has recently been introduced as verso new framework: here, the task is preciso verify whether or not an anonymous document was written by one or several of a series of candidate authors. Mediante some sense, authorship verification redefines the text categorization problem by adding an additional category label: ‘None of the above.’
Per the present context, it should be emphasized that the problem posed by the HA is a ‘vanilla’ example of per problem in authorship verification: while the insieme indeed contains a number of (auto-) attributions, the veracity of all of these has been questioned in previous scholarship
Verification is hence an increasingly common experimental setup in authorship studies, and is the topic of a dedicated track durante the yearly PAN competition, an annual competition on finding computational solutions esatto issues durante present-day textual forensics, mostly related onesto the detection of plagiarism, authorship, and social 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′ con Working Taccuino Papers of the CLEF 2015 Evaluation Labs, anche. L. Cappellato et al. (2015). Generally speaking, authorship verification is a more generic problem than authorship attribution – i.e. every attribution problem could, in principle, be cast as per verification problem – but it has also proven to be more challenging. Con our experiments, we have therefore attempted puro radically minimize any assumptions on our part as preciso 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 sopra the campione.