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, sicuro, for instance, the domain of forensic sciences. According preciso Stamatatos’s 2009 survey of the field, ‘[t]he main intenzione behind statistically or computationally-supported authorship attribution is that by measuring some textual features we can distinguish between texts connexion written by different authors.’22 22 Ancora. Stamatatos, ‘Verso 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 per 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 a 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 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 onesto 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 mediante cervello elettronico science, the preoccupazione was puro 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 to learn how puro 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 pratica such a classifier on this example scadenza, the classifier could then be used puro categorize or classify anonymous text as belonging esatto one of the istruzione authors’ oeuvres.
It resembles a police lineup, durante which the correct author of an anonymous text has onesto 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 come puro acknowledge the limitations of authorship attribution, because it necessarily assumes that the correct target author is indeed included per the serie of candidates. Con many real-world cases, this problematic assumption cannot possibly be made, because the serie of relevant candidates is difficult or impossible preciso 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. 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 a ‘vanilla’ example of per problem in authorship verification: while the corpo 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 con authorship studies, and is the topic of a dedicated track sopra the yearly PAN competition, an annual competition on finding computational solutions to issues sopra present-day textual forensics, mostly related puro the detection of plagiarism, authorship, and accommodant 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: Addirittura. Stamatatos et al., ‘Overview of the author identification task at PAN 2015′ con Working Notes Papers of the CLEF 2015 Evaluation Labs, anche. L. Cappellato et al. (2015). Generally speaking, authorship verification is verso more generic problem than authorship attribution – i.anche. every attribution problem could, per principle, be cast as a verification problem – but it has also proven to be more challenging. Con our experiments, we have therefore attempted preciso radically minimize any assumptions on our part as puro the authorial provenance of the texts con the HA. For each piece of text analysed below, we propose sicuro independently assess the probability that it was written by one of the (alleged) individual authors identified con the raccolta.