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--- |
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annotations_creators: |
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- machine-generated |
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language_creators: |
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- found |
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language: |
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- fr-FR |
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- fr |
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license: |
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- unknown |
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multilinguality: |
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- monolingual |
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pretty_name: COVID-19 French News dataset |
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size_categories: |
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- 10K<n<100K |
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source_datasets: |
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- original |
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task_categories: |
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- text-classification |
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- sequence-modeling |
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- conditional-text-generation |
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task_ids: |
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- topic-classification |
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- multi-label-classification |
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- multi-class-classification |
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- language-modeling |
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- summarization |
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- other-stuctured-to-text |
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--- |
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# Dataset Card for COVID-19 French News dataset |
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## Table of Contents |
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- [Table of Contents](#table-of-contents) |
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- [Dataset Description](#dataset-description) |
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- [Dataset Summary](#dataset-summary) |
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- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) |
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- [Languages](#languages) |
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- [Dataset Structure](#dataset-structure) |
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- [Data Instances](#data-instances) |
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- [Data Fields](#data-fields) |
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- [Data Splits](#data-splits) |
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- [Dataset Creation](#dataset-creation) |
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- [Curation Rationale](#curation-rationale) |
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- [Source Data](#source-data) |
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- [Annotations](#annotations) |
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- [Personal and Sensitive Information](#personal-and-sensitive-information) |
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- [Considerations for Using the Data](#considerations-for-using-the-data) |
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- [Social Impact of Dataset](#social-impact-of-dataset) |
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- [Discussion of Biases](#discussion-of-biases) |
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- [Other Known Limitations](#other-known-limitations) |
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- [Additional Information](#additional-information) |
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- [Dataset Curators](#dataset-curators) |
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- [Licensing Information](#licensing-information) |
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- [Citation Information](#citation-information) |
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- [Contributions](#contributions) |
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## Dataset Description |
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- **Homepage:** |
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- **Repository:** |
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- **Paper:** |
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- **Leaderboard:** |
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- **Point of Contact:** |
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### Dataset Summary |
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The COVID-19 French News dataset is a French-language dataset containing just over 40k unique news articles from more than 50 different French-speaking online newspapers. The dataset has been prepared using [news-please](https://github.com/fhamborg/news-please) - an integrated web crawler and information extractor for news. The current version supports abstractive summarization and topic classification. Dataset Card not finished yet. |
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### Languages |
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The text in the dataset is in French. |
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## Dataset Structure |
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### Data Instances |
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[More Information Needed] |
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### Data Fields |
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- `title`: title of the article |
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- `description`: description or a summary of the article |
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- `text`: the actual article text in raw form |
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- `domain`: source domain of the article (i.e. lemonde.fr) |
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- `url`: article URL, the original URL where it was scraped |
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- `labels`: classification labels |
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## Data Splits |
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COVID-19 French News dataset has only the training set, i.e. it has to be loaded with train split specified: fr_covid_news = load_dataset('gustavecortal/fr_covid_news', split="train") |
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## Dataset Creation |
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### Curation Rationale |
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[More Information Needed] |
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### Source Data |
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#### Initial Data Collection and Normalization |
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[More Information Needed] |
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#### Who are the source language producers? |
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### Annotations |
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#### Annotation process |
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[More Information Needed] |
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### Personal and Sensitive Information |
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As one can imagine, data contains contemporary public figures or individuals who appeared in the news. |
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## Considerations for Using the Data |
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### Social Impact of Dataset |
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The purpose of this dataset is to help researchers develop better French topic classification and abstractive summarization models for news related to COVID-19. |
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### Discussion of Biases |
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[More Information Needed] |
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### Other Known Limitations |
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[More Information Needed] |
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## Additional Information |
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### Dataset Curators |
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The data was originally collected by Gustave Cortal ([email protected]) |
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### Licensing Information |
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Usage of the dataset is restricted to non-commercial research purposes only. |
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### Citation Information |
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``` |
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@dataset{fr_covid_news, |
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author = {Gustave Cortal}, |
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year = {2022}, |
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title = {COVID-19 - French News Dataset}, |
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url = {https://www.gustavecortal.com} |
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} |
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``` |
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### Contributions |
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[@gustavecortal](https://github.com/gustavecortal) |
