Jean Barré
contact@jeanbarre.eu
Fourth year PhD candidate at:
Laboratoire Lattice, CNRS & ENS-PSL, Paris
Supervised by:
Thierry Poibeau and
Thomas Conrad
I work in Computational Literary Studies, combining literary theory with NLP and machine learning to study how narrative forms emerge, circulate, and change across large digital archives.
My PhD, Modeling Genre Literature: Computational Methods and Generic Dynamics in French-Language Fiction, focuses on popular narrative fiction from the late nineteenth to the first half of the twentieth century, with a particular interest in detective and adventure subgenres.
Using large-scale corpora, vector-space models, and network analysis, I trace long-term shifts in textual patterns and character archetypes, such as the emergence and transformations of the detective figure.
Research Interests
Computational Literary Studies
Natural Language Processing
Literary Genre Evolution
Intertextuality
Network Analysis
Computational Humanities
French Literature (19th-20th c.)
Recent Updates
2026/02 | New journal article published!
Toward an Ontological Representation of Fictional Characters (with A. Bourgois, O. Seminck, T. Poibeau) — TL;DR on Bluesky
Toward an Ontological Representation of Fictional Characters (with A. Bourgois, O. Seminck, T. Poibeau) — TL;DR on Bluesky
Software & Projects
Propp-frA tailored NLP pipeline for processing 19th and 20th century French literature. Adapts BookNLP for French novels, including named entity recognition, long coreference resolution, and character attributes extraction.
Website | Publication
Refined Gallica CorpusA curated corpus of 12.000+ French novels from Gallica (BnF's digital library), cleaned and processed for computational literary analysis. Includes metadata enrichment and OCR quality filtering for 19th-20th century fiction. (link TBA)
Research Replication MaterialsCode and data for reproducing key findings from my publications:
Operationalizing Canonicity | Latent Structures of Intertextuality | Detective Archetype
Featured Publications
Modeling the Birth of a Literary Archetype: The Case of the Detective Figure in French Fiction
Barré, J. ; Seminck, O. ; Bourgois, A. ; Poibeau, T. (2025). Conference on Computational Humanities Research (CHR2025).
Proceedings | arXiv | PDF | Github
This figure shows all the detectives in our corpus as dots in a map built from their character embeddings—numerical fingerprints that summarize the verbs, adjectives and nouns most often used around their name in the novels. Three main clusters emerge: one brings together the early, very rational “puzzle-solver” detectives of the late 19th and early 20th century, another groups the more human, empathic investigators of the interwar and mid-century period (like Maigret), and a third contains the later hardboiled and néo-polar detectives, whose language is more physical, colloquial and tied to social violence. The fact that nearby dots tend to come from similar publication years shows that these clusters trace a historical trajectory: as the way authors write about detectives changes, their embeddings drift across the map and form these three successive generations of the archetype.
Barré, J. ; Seminck, O. ; Bourgois, A. ; Poibeau, T. (2025). Conference on Computational Humanities Research (CHR2025).
Proceedings | arXiv | PDF | Github
This figure shows all the detectives in our corpus as dots in a map built from their character embeddings—numerical fingerprints that summarize the verbs, adjectives and nouns most often used around their name in the novels. Three main clusters emerge: one brings together the early, very rational “puzzle-solver” detectives of the late 19th and early 20th century, another groups the more human, empathic investigators of the interwar and mid-century period (like Maigret), and a third contains the later hardboiled and néo-polar detectives, whose language is more physical, colloquial and tied to social violence. The fact that nearby dots tend to come from similar publication years shows that these clusters trace a historical trajectory: as the way authors write about detectives changes, their embeddings drift across the map and form these three successive generations of the archetype.
Cite this work
@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},
journal = {Anthology of Computers and the Humanities},
volume = {3},
pages = {983--999},
editor = {Taylor Arnold, Margherita Fantoli, and Ruben Ros},
doi = {10.63744/SMbYIWcHZj87},
}
Latent Structures of Intertextuality in French Fiction
Barré, J. (2024). Conference on Computational Humanities Research (CHR 2024), Aarhus, Denmark.
Proceedings | ArXiv | PDF
This figure shows how much each novel “resembles” other novels published before and after it, and compares two groups: canonical works (blue) and the rest of the archive (orange). For every book, we turn its text into a numerical vector and measure how similar it is to novels from different years, centering the graph on its publication date (0 on the x-axis). Both curves peak around the year of publication: books look most like the novels of their own time. But after that, the blue curve stays higher than the orange one: canonical novels remain more similar to later fiction than ordinary novels do. In other words, once they appear, canonical works keep “speaking the language” of future literature for longer, while most other books fade more quickly from the intertextual landscape.
Barré, J. (2024). Conference on Computational Humanities Research (CHR 2024), Aarhus, Denmark.
Proceedings | ArXiv | PDF
Cite this work
@inproceedings{barre_latentstructuresintertextuality_2024,
location = {Aarhus},
title = {Latent Structures of Intertextuality in French Fiction},
rights = {Creative Commons Attribution 4.0 International},
eventtitle = {{CHR} 2024},
pages = {21--26},
booktitle = {Proceedings of the Computational Humanities Research Conference 2024},
author = {Barré, Jean},
date = {2024},
url={https://ceur-ws.org/Vol-3834/paper97.pdf},
keywords = {notion, Computation and Language (cs.{CL}), {FOS}: Computer and information sciences},
}
Operationalizing Canonicity: A Quantitative Study of French 19th and 20th Century Literature
Barré, J. ; Camps, JB. ; Poibeau, T. (2023). Journal of Cultural Analytics, 8(1).
DOI | PDF
This figure zooms in on a single author, Colette, and maps each of her novels as a point in a 2D space built from their writing style (using the same kind of text-based features as in the main model). The blue dots are the novels that later became canonical, the orange ones are the rest. On this map, Colette’s canonical books cluster tightly together, mostly in a region corresponding to works from the late 1920s–1930s, while earlier popular series like Claudine sit farther away. This suggests that even within one author’s oeuvre, only a subset of texts shares the stylistic “signature” that institutions tend to select and preserve as canonical.
Barré, J. ; Camps, JB. ; Poibeau, T. (2023). Journal of Cultural Analytics, 8(1).
DOI | PDF
Cite this work
@article{barre_operationalizingcanonicityquantitative_2023,
title = {Operationalizing Canonicity: A Quantitative Study of French 19th and 20th Century Literature},
volume = {8},
doi = {10.22148/001c.88113},
shorttitle = {Operationalizing Canonicity},
pages = {1--29},
number = {1},
journaltitle = {Journal of Cultural Analytics},
author = {Barré, Jean and Camps, Jean-Baptiste and Poibeau, Thierry},
date = {2023},
langid = {english},
keywords = {canon},
}