Anke Holler, Caroline Sporleder & Benjamin Gittel

“All happy families are alike, each unhappy family is unhappy in its own way,” is the first sentence of Tolstoy’s “Anna Karenina” and one of the most talked about examples of reflection in fictional literature. Although even lay people distinguish such reflective passages in novels from passages that report actions or describe characters, reflective passages have not yet been established as a research topic in their own right in literary studies. Against this backdrop the project will combine insights from literary studies, linguistics, computational modelling and quantitative as well as qualitative text analysis to (i) elaborate and formalise a comprehensive concept of reflective passage, (ii) identify and classify such reflective passages in narrative fiction and (iii) explain their patterns of occurrence in roughly 350 years of literary history. To this end, the project will build on previous work for identifying reflection automatically in other text types as well as work on detecting related phenomena such as genericity and epistemic status and extend and combine these in a linguistically informed machine learning framework for finding author/narrator-attributed and character-attributed reflective passages in narrative fiction. By applying our models to a large corpus of German literature spanning several centuries, we will be able to identify periods in which reflection was particularly prevalent (“boom periods”). We will also look more closely at two prominent variants of reflective storytelling in literary history: essayistic and encyclopedic narration. We will compare automatically identified essayistic and encyclopedic passages in narrative fiction to non-fictional essays and encyclopedic texts and investigate similarities and differences with respect to style, topic and the epistemic status of clauses in order to identify internal as well as external functions of these passages in relation to the literary works and their socio-cultural context.   Our contribution to the overall Priority Program “Computational Literary Studies” consists in (i) operationalizing a basic concept from literary theory by performing a qualitative and quantitative corpus study, (ii) enriching the methodic options to structure literary texts,  (iii) developing novel computational models for detecting reflection and related phenomena and demonstrating the usefulness of these algorithmic methods for literary historiography as well as the integration of their results into the qualitative research process, and (iv) creating and releasing a corpus manually annotated for reflection.