@inproceedings{feldkamp-etal-2025-fact,
    title = "Fact from Fiction: Finding Serialized Novels in Newspapers",
    author = "Feldkamp, Pascale  and
      Lassche, Alie  and
      Baunvig, Katrine Fr{\o}kj{\ae}r  and
      Nielbo, Kristoffer  and
      Bizzoni, Yuri",
    editor = "Zhao, Jin  and
      Wang, Mingyang  and
      Liu, Zhu",
    booktitle = "Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/landing_page/2025.acl-srw.45/",
    pages = "695--707",
    ISBN = "979-8-89176-254-1",
    abstract = "Digitized literary corpora of the 19th century favor canonical and novelistic forms, 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."
}