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This thesis deals with network science approaches to literary corpus analysis. In an at-scale approach, it uses intermediate resolution levels to combine the advantages of both hermeneutical and statistical tools in a mixed-methods approach to release synergies. The Deutsche Novellenschatz, a collection of 19th century German language novellas, will be the starting point of the analyses. The texts where edited and published by Paul Heyse and Hermann Kurz between 1871 and 1876 in 24 volumes. The corpus was digitized by Weitin in 2016 and is part of the Deutsche Textarchiv (German text archive). Investigating structural properties of this corpus will lead to analyses that help to understand whether these properties resonate with the intentions of the editors in respect of quality and delimitation for the novella genre. A key tool in the at-scale approach will be network analysis to consider different levels of examination from single texts to the entire corpus. More concrete, the thesis can be split into three parts. Each part takes a certain viewpoint to disentangle the object of study. First, we try to validate the underlying novella theory by a reading experiment. The editors claim that a novella is characterized by the fact that it can be summarized within a few sentences. The presented study shows that this can only hold under certain circumstances. While it is possible that the claim was made as a general principal, we converted their recommended procedure into a hypothesis. In that way, we tested the summarizability of Hieronymus Lorm’s novella Ein adeliges Fräulein. As a result, we observed that only frequent readers agree on content and ordering of the summaries. In the second research project, we analyze the entire corpus with stylometric distance measures. The goal of this is twofold. On the one hand, it makes it possible to gain new insights into the corpus. On the other hand, we could use the Novellenschatz as a prime example of a closed corpus. As such, it is used to gain a deeper understanding about ...
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