English Bards and Unknown Reviewers: a Stylometric Analysis of Thomas Moore and the Christabel Review

Fraught relations between authors and critics are a commonplace of literary history. The particular case that we discuss in this article, a negative review of Samuel Taylor Coleridge's Christabel (1816), has an additional point of interest beyond the usual mixture of amusement and resentment that surrounds a critical rebuke: the authorship of the review remains, to this day, uncertain. The purpose of this article is to investigate the possible candidacy of Thomas Moore as the author of the provocative review. It seeks to solve a puzzle of almost two hundred years, and in the process clear a valuable scholarly path in Irish Studies, Romanticism, and in our understanding of Moore's role in a prominent literary controversy of the age

GPT-2: Girl Detective Analyzing AI-Generated Nancy Drew with Stylometry

Writing styles are often viewed as unique to their writers–a compositional fingerprint of sorts. An analytical tool based upon this assumption is stylometry: the statistical analysis of the variations in the literary styles of works, often used to determine the most likely author of a particular work. Stylometric techniques abound in a multitude of fields, including history, literary studies, and even courts of law. Stylometry is often used as a form of evidence as to the identities of authors of written material pertaining to legal cases, a famous example being the conviction of the Unabomber based upon stylistic similarities between his earlier essays and his famous manuscript [1]. Thus, stylometric techniques are ascribed a lot of power. But, what if stylometry isn’t as dependable as it is assumed to be? What if a writer’s so-called “unique” style can be easily imitated to fool stylometric tools? In this project, we aim to analyze the ability of AI to generate text stylometrically consistent with the writer upon whom it was trained

Finn’s Hotel and the Joycean Canon

Initially, I conduct a stylometric analysis of Dubliners, A Portrait of the Artist as a Young Man, Ulysses, Finnegans Wake, and Finn’s Hotel, using the relative frequencies of the 100 most frequent words in each text to form an authorial signature. In doing so, I hope to demonstrate whether the collection is, from the perspective of style, quite distinct, or alternatively, closely aligned to Finnegans Wake. If style can be considered a determinant of what makes a text, then I believe that the results of such an analysis should be accepted as an indicator of whether Joyce intended Finn’s Hotel to be a standalone publication, or whether the relevant manuscripts are indeed the earliest incarnations of what would eventually come to be Finnegans Wake

The effect of training set size in authorship attribution: application on short arabic texts

Authorship attribution (AA) is a subfield of linguistics analysis, aiming to identify the original author among a set of candidate authors. Several research papers were published and several methods and models were developed for many languages. However, the number of related works for Arabic is limited. Moreover, investigating the impact of short words length and training set size is not well addressed. To the best of our knowledge, no published works or researches, in this direction or even in other languages, are available. Therefore, we propose to investigate this effect, taking into account different stylomatric combination. The Mahalanobis distance (MD), Linear Regression (LR), and Multilayer Perceptron (MP) are selected as AA classifiers. During the experiment, the training dataset size is increased and the accuracy of the classifiers is recorded. The results are quite interesting and show different classifiers behaviours. Combining word-based stylomatric features with n-grams provides the best accuracy reached in average 93%

Authorship Attribution: Specifics for Slovene

The paper shows the importance of a quality analysis of linguistic features which enable the process of authorship attribution or author profiling in a forensic, literary or economic context (anonymous threat letters, plagiarism, literary works of unknown authorship, client profiling). It also highlights the lack of realized analyses for Slovene and outlines the methodology of detecting the syntactic, lexical, semantic and character features in order to quantify the author’s personal styl