Interdisciplinary Research into French News Media Ecosystems
Datasets, benchmarks and open models for studying the French press.
Non-profit association under French law (loi 1901) · Paris · RNA W751279600
Supported by
- Project 4beta by Oxylabs
- Amazon Web Services
- Microsoftfor Nonprofits
- ElevenLabs
Research infrastructure
Le French News Lab explores how French news shapes political life. Our work looks at the stories, frames, and language that structure public debate, combining computational methods with media and political analysis.
We develop datasets, methods, and public-facing research that make the French media ecosystem easier to study, question, and understand.
Framing Studies
Narrative construction patterns
Research Infrastructure
Benchmarks, datasets, and models for comparative analysis
Political Classification
Expert consensus methods
Announcement
Le French News Lab wins access to France’s Jean Zay supercomputer
GENCI has awarded Le French News Lab computing time on Jean Zay, bringing France’s national supercomputing infrastructure to our research on French news.
Read the announcementTwo papers accepted for oral presentation at the International Conference on Natural Language and Speech Processing 2026
FrIdéo and Framing by Wording, Framing by Selection, both accepted for oral presentation.
Le French News Lab introduces FrenchNews-7
87,637 articles from 13 publishers, harmonised into 7 shared editorial desk categories.
FrIdéo: French News Outlet Ideology Scoring via Multi-Source Evidence Fusion and Distancing-Aware Lexical Scoring
A continuous, auditable ideology scale for French national news, fusing nine evidence families and separating partisan endorsement from critical reporting. Accepted for oral presentation at ICNLSP 2026.
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All publications
What we do
We build the measurement infrastructure that makes the French news ecosystem possible to study: annotated corpora, reproducible benchmarks, open models, and peer-reviewed methods for questions that are usually argued about without evidence.
Measurement before argument
Claims about bias, framing and slant in the French press are usually made without a number anyone can check. We build scales and benchmarks that are documented, versioned and auditable, so that a disagreement about the media can become a disagreement about data.
Methods you can check
Papers are published with the datasets behind them. Results are reported as means across multiple random seeds rather than a single best run, because a number that only appears once is not a result.
Released in the open
Our datasets and models are published on Hugging Face, data.gouv.fr and Kaggle under open licences, free to use. Nothing on this site is behind a paywall or a signup form.
Recent work
Papers on framing, ideology and topic classification in the French press.
Framing by Wording, Framing by Selection: A Large-Scale Two-Dimensional Audit of French News Headlines, 2022–2025
A two-dimensional audit separating how French news headlines are worded from which stories get covered, with a released 10,000-headline supervision set and a reusable recalibration protocol. Accepted for oral presentation at ICNLSP 2026.
Read the paperFrenchNews-7: Benchmarking Cross-Publisher French News Editorial Desk Classification
Le French News Lab's first research publication introduces FrenchNews-7, a cross-publisher French news classification benchmark with 87,637 articles from 13 publishers and a public CamemBERT classifier by Amr Sobhy.
Read the paperConflict or Strategy? Asymmetric Role Framing of La France insoumise and Rassemblement National in French News Headlines, 2022–2025
A quantitative framing analysis of 28,592 headlines about LFI and RN across 25 French outlets (2022-2025), showing systematic asymmetric framing patterns in the French press.
Read the paperOpen data and models
Everything we build for a paper is released alongside it. These are the current public datasets and models — free to download, with data dictionaries and full metadata.
FrenchNews-7 corpus
A cross-publisher corpus of French news articles annotated by editorial desk, built so that topic classifiers can be tested on publishers they were never trained on — the case where reported accuracy usually falls apart. Released with the train and test splits used in the paper.
From the paper →CamemBERT FrenchNews-7 model
A CamemBERT-base classifier fine-tuned on FrenchNews-7 for editorial desk classification, published with its model card and the per-seed evaluation scores reported in the paper.
FrIdéo ideology scores
Continuous ideology scores for thirty French national news outlets, fusing nine independent families of evidence rather than resting on any single one. Published as CSV and JSON with a data dictionary and full metadata, under CC BY 4.0.
From the paper →Work with us
We collaborate with researchers, journalists, civil-society organisations and academic institutions working on the French information ecosystem. If you want to use our data, replicate a result, or propose a study, get in touch — we answer every message.