@inproceedings{gordon-2026-tracing,
    title = "Tracing Thematic Change in Early {E}nglish-Language Science Fiction, 1818-1930",
    author = "Gordon, Jonathan",
    editor = {Hamilton, Sil  and
      {\"O}hman, Emily  and
      Hicke, Rebecca M. M.  and
      Bizzoni, Yuri  and
      Bax, Axel  and
      Matthews, Jacob A.  and
      H{\"a}m{\"a}l{\"a}inen, Mika},
    booktitle = "Proceedings of the 6th International Conference on Natural Language Processing for the Digital Humanities",
    month = jul,
    year = "2026",
    address = "San Diego, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl-workshops/2026.nlp4dh-1.21/",
    pages = "226--235",
    ISBN = "979-8-89176-427-9",
    abstract = "How did the thematic repertoire of early English-language science fiction change as the genre consolidated between 1818 and 1930? Using a corpus of 238 public-domain texts, we apply temporally binned latent Dirichlet allocation (LDA), comparing models with and without Authorless preprocessing (which probabilistically downweights author-specific vocabulary). Cross-period topic alignments exceed a permutation null baseline, indicating continuity in topic structure over time. Full-corpus LDA can produce comparable per-topic quality, but only temporal binning enables diachronic alignment; within the binned setting, Authorless reduces author concentration and modestly increases the share of thematic topics without materially reducing coherence. Four high-continuity topic chains {--} centered on mobility, affect, planetary scale, and scientific knowledge {--} suggest a shift from earlier romantic and speculative concerns toward more consolidated technoscientific forms. These chains generate interpretable hypotheses about the literary history of early science fiction, and the workflow supports diachronic analysis in small, author-skewed corpora."
}