A Mixed Methods Design for Computational Genre Stylistics and Unstructured Genres. Towards a Functional History of 19th Century German Novellas.

• Applicant: Professor Dr. Julian Schröter
• Subject Area: German Literary and Cultural Studies (Modern German Literature)
• Term: from 2020 to 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 449668519

The German novella, which is actually split up into two genres, that of the ›Novelle‹ and that of the ›Erzählung‹, is a highly controversial genre. One academic group believes that the Novelle is the most stringent form of prose fiction. This group claims that there has to be acknowledged a fundamental difference between the strictly defined ›Novelle‹ and the more loose field of the ›Erzählungen‹. In contradiction to the first group, the second academic group believes that ›Novelle‹ and ›Erzählung‹ are not different genres but one amorphous mass. The general goal of the project is to understand and to clarify this contradiction. Up to now, research has overlooked one central aspect that helps to understand this contradiction: There is a dialectical structure at the core of the concepts of ›Novelle‹ and ›Erzählung‹ with regard to the relationship between poetics and reading practice. The structure is dialectical, because the poetological concept and reading experience do not match in the case of ›Novellen‹. In the 19th century, writers and readers had a sense of this dialectics: They had strong expectations regarding the aesthetic uniformity of ›Novellen‹ within poetological discourse, but acknowledged at the same time that these expectations were disappointed in practice. The concept of ›Erzählung‹ lacks this dialectical structure. The project will describe and explain this dialectics and thus yield a deeper understanding of the cultural structure of historical genres. I will try to reach this goal by two tasks:The first task is to elaborate a mixed methods design that allows to connect three dimensions: the use of genre labels, textual features, and medial and social context factors. The second task is to develop the requisite methodology of data modeling. Up to now, computational genre stylistics has been modeling textual features mostly as document-term-matrices based on bag of words models. However, this modeling does not suit for testing hypotheses on the dialectical structure of German novellas, because the bag of words model does not transparently represent structural, content based, and poetological genre features. Therefore, genre features which are presumed to be relevant to the semantics of ›Novelle‹ and ›Erzählung‹ have to be modeled. Based on the modeling and operationalization of genre features, empirical hypotheses on the dialectical structure of the relevant genre concepts are tested. Finally, the change of the genre semantics and practices is worked out as the conceptual history of the German novella genres. This final step is based on an adaption of supervised machine learning, which is also called ›perspectival modeling‹.In this way, the project will help to better understand the actual rules of the use of genre concepts in literary history, and it will also offer the requisite but not yet available methodology of a computational, context oriented, and historical analysis of loosely structured genres.

• DFG Programme: WBP Fellowship
• International Connection: Canada
• Hosts: Professor Dr. Thomas Ernst, from 3/2022 until 8/2022; Professor Dr. Mike Kestemont, from 3/2022 until 8/2022; Professor Ted Underwood, Ph.D., from 8/2022 until 2/2023