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Anonymity, individuality and commonality in writing in British periodicals - 1830 to 1890: a computational stylistics approachAntonia, Alexis January 2009 (has links)
Research Doctorate - Doctor of Philosophy (PhD) / The aim of the thesis is to use computational stylistics, and in particular the methods pioneered by John Burrows, to explore aspects of the nineteenth-century periodical genre. Published for the most part anonymously, periodical articles were written by an extraordinary range of authors on an incredible variety of topics. The standard of writing in the thousands of articles appearing in the ‘higher’ or ‘literary’ journals has generally been agreed by scholars to be ‘remarkably good’. Beginning in 1802 and flourishing for most of the century, this outstanding genre of writing had all but disappeared by the beginning of the twentieth century. The text collection for the thesis consists of almost two million words by twenty-two authors. My study employs a variety of statistical tests on these texts to examine the effect of such factors as anonymity, commonality, authorial individuality, gender, house-style, text-type and chronology on the periodicals. I begin by taking a broad view of the field: first allowing the articles to ‘speak for themselves’ and to exhibit their commonalities and individual differences; then exploring the significance of both the intra-generic focus of the article – the stance taken in a particular article – and the author’s own idiosyncratic preferences in determining the incidence of function words in these articles. The interplay between these two factors provided an explanation as to why the articles of some authors invariably grouped together while those of other authors displayed marked variability. The use of lists of authorial ‘marker words’ – those words used relatively more or relatively less frequently by individual authors – showed that one can think of this large group of mostly anonymous periodical articles as a set of authorial oeuvres. I also look at the frequently made assertion that authors adapted their writing to the ‘house style’ of particular journals, and come to the conclusion that it does not significantly affect the deeper level of style revealed by function word usage. I then examine the question of whether or not there are differences between men’s and women’s usages of function words, coming to the conclusion that, although differences can be seen to exist, it is not at present possible to come up with sets of ‘marker words’ that reveal gender in the way that is possible with authorship. I use ‘marker words’ to identify the characteristics of one major author, George Eliot, and to show how she modified her stylistic practices when she moved from the periodical essay to fiction. I demonstrate how the techniques of computational stylistics can be used to check the legitimacy of some of the attributions made in the Wellesley Index, and I attribute one much-discussed anonymous group of articles on ‘the woman question’ to Robert Cecil 3rd Marquess of Salisbury and Prime Minister of England.
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On Computational Stylistics : mining Literary Texts for the Extraction of Characterizing Stylistic Patterns / De la stylistique computationnelle : fouille de textes littéraires pour l'extraction de motifs stylistiques caractérisantsBoukhaled, Mohamed Amine 13 September 2016 (has links)
Notre thèse se situe dans le domaine interdisciplinaire de la stylistique computationnelle, à savoir l'application des méthodes statistiques et computationnelles à l'étude du style littéraire. Historiquement, la plupart des travaux effectués en stylistique computationnelle se sont concentrés sur les aspects lexicaux. Dans notre thèse, l’accent est mis sur l'aspect syntaxique du style qui est beaucoup plus difficile à analyser étant donné sa nature abstraite. Comme contribution principale, dans cette thèse, nous travaillons sur une approche à l'étude stylistique computationnelle de textes classiques de littérature française d'un point de vue herméneutique, où découvrir des traits linguistiques intéressants se fait sans aucune connaissance préalable. Plus concrètement, nous nous concentrons sur le développement et l'extraction des motifs morphosyntaxiques. Suivant la ligne de pensée herméneutique, nous proposons un processus de découverte de connaissances pour la caractérisation stylistique accentué sur la dimension syntaxique du style et permettant d'extraire des motifs pertinents à partir d'un texte donné. Ce processus proposé consiste en deux étapes principales, une étape d'extraction de motifs séquentiels suivi de l'application de certaines mesures d'intérêt. En particulier, l'extraction de tous les motifs syntaxiques possibles d'une longueur donnée est proposée comme un moyen particulièrement utile pour extraire des caractéristiques intéressantes dans un scénario exploratoire. Nous proposons, évaluons et présentons des résultats sur les trois mesures d'intérêt proposées, basée chacune sur un raisonnement théorique linguistique et statistique différent. / The present thesis locates itself in the interdisciplinary field of computational stylistics, namely the application of statistical and computational methods to the study of literary style. Historically, most of the work done in computational stylistics has been focused on lexical aspects especially in the early decades of the discipline. However, in this thesis, our focus is put on the syntactic aspect of style which is quite much harder to capture and to analyze given its abstract nature. As main contribution, we work on an approach to the computational stylistic study of classic French literary texts based on a hermeneutic point of view, in which discovering interesting linguistic patterns is done without any prior knowledge. More concretely, we focus on the development and the extraction of complex yet computationally feasible stylistic features that are linguistically motivated, namely morpho-syntactic patterns. Following the hermeneutic line of thought, we propose a knowledge discovery process for the stylistic characterization with an emphasis on the syntactic dimension of style by extracting relevant patterns from a given text. This knowledge discovery process consists of two main steps, a sequential pattern mining step followed by the application of some interestingness measures. In particular, the extraction of all possible syntactic patterns of a given length is proposed as a particularly useful way to extract interesting features in an exploratory scenario. We propose, carry out an experimental evaluation and report results on three proposed interestingness measures, each of which is based on a different theoretical linguistic and statistical backgrounds.
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Latent Semantic Analysis, Corpus stylistics and Machine Learning Stylometry for Translational and Authorial Style Analysis: The Case of Denys Johnson-Davies’ Translations into EnglishAl Batineh, Mohammed S. 22 April 2015 (has links)
No description available.
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