"Genre Analysis and Corpus Design: 19th Century Spanish American Novels (1830-1910)."
Kontaktadresse an der Universität Würzburg:
Institut für Deutsche Philologie
Lehrstuhl für Computerphilologie
Am Hubland - 97074 Würzburg
Erstbetreuer: Prof. Dr. Christof Schöch (Univ. Trier)
Klasse in der Graduiertenschule: „Philosophie, Sprachen, Künste“
Promotion in der Graduiertenschule ab SS 2016.
This dissertation in the field of Digital Literary Stylistics is concerned with theoretical concerns of literary genre, with the design of a corpus of 19th-century Spanish American novels, and with its empirical analysis in terms of subgenres of the novel. The digital text corpus consists of 256 Argentine, Cuban, and Mexican novels from the period between 1830 and 1910. It has been created with the goal to analyze thematic subgenres and literary currents that were represented in numerous novels in the 19th century by means of computational text categorization methods. The texts have been gathered from different sources, encoded in the standard of the Text Encoding Initiative (TEI), and enriched with detailed bibliographic and subgenre-related metadata, as well as with structural information.
To categorize the texts, statistical classification and a family resemblance analysis relying on network analysis are used with the aim to examine how the subgenres, which are understood as communicative, conventional phenomena, can be captured on the stylistic, textual level of the novels that participate in them. The result is that both thematic subgenres and literary currents are textually coherent to degrees of 70-90 %, depending on the individual subgenre constellation.
Besides the empirical focus, the dissertation also aims to relate literary theoretical genre concepts to the ones used in Digital Genre Stylistics as a subfield of Digital Humanities. It is argued that literary text types, conventional literary genres, and textual literary genres should be distinguished on a theoretical level to improve the conceptualization of genre for digital text analysis.