Use Cases

Detective Archetype

Modeling the Construction of a Literary Archetype: The Case of the Detective Figure in French Literature

This research explores the evolution of the detective archetype in French detective fiction through computational analysis. Using quantitative methods and character-level embeddings, we show that a supervised model is able to capture the unity of the detective archetype across 150 years of literature, from M. Lecoq (1866) to Commissaire Adamsberg (2017). Building on this finding, the study demonstrates how the detective figure evolves from a secondary narrative role to become the central character and the “reasoning machine” of the classical detective story. In the aftermath of the Second World War, with the importation of the hardboiled tradition into France, the archetype becomes more complex, navigating the genre’s turn toward social violence and moral ambiguity.

@article{barre_detectives_2025,
  title = {Modeling the Construction of a Literary Archetype: The Case of the Detective Figure in French Literature},
  author = {Jean Barré and Olga Seminck and Antoine Bourgois and Thierry Poibeau},
  year = {2025},
  address = "Luxembourg",
  journal = {Anthology of Computers and the Humanities},
  volume = {3},
  pages = {983--999},
  editor = {Taylor Arnold, Margherita Fantoli, and Ruben Ros},
  doi = {10.63744/SMbYIWcHZj87},
  url = {https://anthology.ach.org/volumes/vol0003/modeling-construction-of-literary-archetype-case/},
}

Character Representation - Ontology

Toward an ontological representation of fictional characters

Characters are central to narrative theory but remain under-specified in computational work, where they are often reduced to clusters of words or vectors. We propose an operationalizable ontology of characterization that bridges narratological theory and NLP. From BERT-based clustering of character descriptions, we derive 17 classes of attributes (actions, emotions, traits, relations, possessions, etc.), validated through manual annotation (𝑘 =0.77) and automatic classification (64% accuracy vs. 12% baseline). Applied to character similarity tasks for French fiction, our framework outperforms existing models. By aligning narratological insights with computational methods, we move toward a representation of fictional characters as structured, comparable entities for large-scale literary analysis.

@article{bourgois2026,
  author  = {Bourgois, Antoine and Barré, Jean and Seminck, Olga and Poibeau, Thierry},
  title   = {Toward an ontological representation of fictional characters},
  journal = {Computational Humanities Research},
  year    = {2026},
  volume  = {2},
  pages   = {e6},
  doi     = {10.1017/chr.2026.10025},
  url     = {https://www.cambridge.org/core/journals/computational-humanities-research/article/toward-an-ontological-representation-of-fictional-characters/EF9F289D4EA7FC0A6ECC38BAA391DF76}
}