Update README.md

README.md

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 ---
+language:
+- en
 license: cc-by-nc-nd-4.0
+pretty_name: PoliticalDebatesCorpus-EN — English Political Debates Corpus
+size_categories:
+- 10B<n<100B
+task_categories:
+- text-generation
+- fill-mask
+- text-classification
+tags:
+- political-discourse
+- parliamentary-debates
+- argument-mining
+- stance-detection
+- domain-specific
+- pretraining
 ---
+
+# RooseDebates: English Political Debates Corpus
+
+PoliticalDebatesCorpus-EN is a large-scale English corpus of political debate and speech transcripts,
+assembled for domain-specific language model pre-training. It is the training corpus behind
+**RooseBERT**, a language model tailored to the dialogic and argumentative nature of political
+debates. The corpus brings together televised presidential debates and parliamentary debates
+from multiple countries and international bodies, totalling **~11 GB** of text and spanning the
+period **1946–2025**.
+
+## Dataset Summary
+
+- **Total size:** ~11 GB of cleaned English text
+- **Time span:** 1946–2025
+- **Domain:** Political debates, parliamentary sessions, presidential debates, UN debates
+- **Languages:** English
+- **Source types:** Televised exchanges, parliamentary debates, primary/general election debates
+- **Intended use:** Pre-training and fine-tuning of language models for political discourse analysis
+
+All sources originate from authoritative speakers and official political settings, where
+political decisions are discussed, contested, and communicated to the public.
+
+## Supported Tasks
+
+The corpus was designed to support domain-adaptive pre-training for downstream tasks including:
+
+- **Stance detection** (support / oppose toward a target)
+- **Sentiment analysis** of debate speeches
+- **Argument component detection and classification** (claims vs. premises)
+- **Argument relation prediction and classification** (support / attack / no-relation)
+- **Motion policy classification**
+- **Named entity recognition (NER)**
+
+## Data Sources
+
+The corpus combines existing curated collections with transcripts scraped from official debate
+websites. Each source was pre-processed to remove hyperlinks and markup tags and to collapse
+multiple spaces.
+
+| Source | Coverage | Period | Size |
+|---|---|---|---|
+| African Parliamentary Debates (HOME Project) | Ghana & South Africa | 1999–2024 | 573 MB |
+| Australian Parliamentary Debates | Australia | 1998–2025 | 1 GB |
+| Canadian Parliamentary Debates (OpenParliament) | Canada | 1994–2025 | 1.1 GB |
+| European Parliamentary Debates (EUSpeech) | EU leaders & institutions | 2007–2015 | 110 MB |
+| Irish Parliamentary Debates (ParlEE + Dáil Éireann DB) | Ireland | 1919–2019 | ~3.4 GB |
+| New Zealand Parliamentary Debates (ParlSpeech) | New Zealand | 1987–2019 | 791 MB |
+| Scottish Parliamentary Debates (ParlScot) | Scotland | until 2021 | 443 MB |
+| UK Parliamentary Debates (House of Commons) | United Kingdom | 1979–2019 | 2.6 GB |
+| UN General Debate Corpus (UNGDC) | UN General Assembly | 1946–2023 | 186 MB |
+| UN Security Council Debates (UNSC) | UN Security Council | 1992–2023 | 387 MB |
+| United States Debates (American Presidency Project) | United States | 1960–2024 | 16 MB |
+
+## Pre-processing
+
+Each dataset was cleaned with a uniform pipeline:
+
+1. Removal of hyperlinks and markup tags
+2. Collapsing of multiple consecutive whitespace characters
+3. Merging of per-source splits into a unified corpus with balanced representation across sources
+
+## Intended Uses & Limitations
+
+**Intended uses.** Pre-training or continued pre-training of encoder-based language models for
+political discourse analysis; fine-tuning on stance, sentiment, argument mining, and policy
+classification tasks.
+
+**Limitations.**
+
+- The corpus is **English-only** and skewed toward Commonwealth and U.S./UN sources, so
+  geographic and linguistic coverage is uneven.
+- Transcripts reflect the political opinions and rhetoric of the speakers; the corpus is **not**
+  a neutral source and may contain biased, adversarial, or offensive language.
+- Time coverage varies by source, which may introduce period-specific framing effects.
+- Models trained on this data should not be treated as authoritative on factual political claims.
+
+## Licensing
+
+This corpus aggregates multiple underlying datasets, each released under its own terms by its
+original authors. **Users must review and comply with the license of each constituent source**
+before redistribution or commercial use. The aggregation and accompanying card are released
+under CC-BY-NC-ND-4.0; this does not override the licenses of the individual sources.
+
+## Citation
+
+If you use this dataset, please cite us:
+
+```bibtex
+@article{dore2025roosebert,
+  title={RooseBERT: A New Deal For Political Language Modelling},
+  author={Dore, Deborah and Cabrio, Elena and Villata, Serena},
+  journal={arXiv preprint arXiv:2508.03250},
+  year={2025}
+}
+```
+
+Please also cite the original sources of the constituent datasets where appropriate (see the
+**Data Sources** table and the references in the paper).
+
+## Contact
+
+Deborah Dore - deborah.dore@cnrs.fr