Fact from Fiction: Finding Serialized Novels in Newspapers

Abstract

Digitized literary corpora of the 19th century favor canonical novels published in standalone volumes, sidelining a broader and more diverse literary production. Serialized fiction – widely read but embedded in newspapers – remains especially underexplored, particularly in low-resource languages like Danish. This paper addresses this gap by developing methods to identify fiction in digitized Danish newspapers (1818–1848). We (1) introduce a manually annotated dataset of 1,394 articles and (2) evaluate classification pipelines using both selected linguistic features and embeddings, achieving F1-scores of up to 0.91. Finally, we (3) analyze feuilleton fiction via interpretable features to test its drift in discourse from neighboring nonfiction. Our results support the construction of alternative literary corpora and contribute to ongoing work on modeling the fiction–nonfiction boundary by operationalizing discourse-level distinctions at scale.