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--- |
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annotations_creators: |
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- crowdsourced |
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- expert-generated |
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language_creators: |
|
- found |
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language: |
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- en |
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license: |
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- cc-by-4.0 |
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multilinguality: |
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- monolingual |
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size_categories: |
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- 1M<n<10M |
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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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task_ids: [] |
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pretty_name: HyperpartisanNewsDetection |
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tags: |
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- bias-classification |
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dataset_info: |
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- config_name: byarticle |
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features: |
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- name: text |
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dtype: string |
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- name: title |
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dtype: string |
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- name: hyperpartisan |
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dtype: bool |
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- name: url |
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dtype: string |
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- name: published_at |
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dtype: string |
|
splits: |
|
- name: train |
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num_bytes: 2803943 |
|
num_examples: 645 |
|
download_size: 1000352 |
|
dataset_size: 2803943 |
|
- config_name: bypublisher |
|
features: |
|
- name: text |
|
dtype: string |
|
- name: title |
|
dtype: string |
|
- name: hyperpartisan |
|
dtype: bool |
|
- name: url |
|
dtype: string |
|
- name: published_at |
|
dtype: string |
|
- name: bias |
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dtype: |
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class_label: |
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names: |
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'0': right |
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'1': right-center |
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'2': least |
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'3': left-center |
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'4': left |
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splits: |
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- name: train |
|
num_bytes: 2805711609 |
|
num_examples: 600000 |
|
- name: validation |
|
num_bytes: 960356598 |
|
num_examples: 150000 |
|
download_size: 1003195420 |
|
dataset_size: 5611423218 |
|
--- |
|
|
|
# Dataset Card for "hyperpartisan_news_detection" |
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|
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## 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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|
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## Dataset Description |
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|
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- **Homepage:** [https://pan.webis.de/semeval19/semeval19-web/](https://pan.webis.de/semeval19/semeval19-web/) |
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- **Repository:** https://github.com/pan-webis-de/pan-code/tree/master/semeval19 |
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- **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
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- **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
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- **Size of downloaded dataset files:** 1.00 GB |
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- **Size of the generated dataset:** 5.61 GB |
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- **Total amount of disk used:** 6.62 GB |
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|
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### Dataset Summary |
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|
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Hyperpartisan News Detection was a dataset created for PAN @ SemEval 2019 Task 4. |
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Given a news article text, decide whether it follows a hyperpartisan argumentation, i.e., whether it exhibits blind, prejudiced, or unreasoning allegiance to one party, faction, cause, or person. |
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|
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There are 2 parts: |
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- byarticle: Labeled through crowdsourcing on an article basis. The data contains only articles for which a consensus among the crowdsourcing workers existed. |
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- bypublisher: Labeled by the overall bias of the publisher as provided by BuzzFeed journalists or MediaBiasFactCheck.com. |
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|
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### Supported Tasks and Leaderboards |
|
|
|
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
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|
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### Languages |
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|
|
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
|
|
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## Dataset Structure |
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|
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### Data Instances |
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|
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#### byarticle |
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|
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- **Size of downloaded dataset files:** 1.00 MB |
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- **Size of the generated dataset:** 2.80 MB |
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- **Total amount of disk used:** 3.81 MB |
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|
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An example of 'train' looks as follows. |
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``` |
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This example was too long and was cropped: |
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|
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{ |
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"hyperpartisan": true, |
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"published_at": "2020-01-01", |
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"text": "\"<p>This is a sample article which will contain lots of text</p>\\n \\n<p>Lorem ipsum dolor sit amet, consectetur adipiscing el...", |
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"title": "Example article 1", |
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"url": "http://www.example.com/example1" |
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} |
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``` |
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|
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#### bypublisher |
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|
|
- **Size of downloaded dataset files:** 1.00 GB |
|
- **Size of the generated dataset:** 5.61 GB |
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- **Total amount of disk used:** 6.61 GB |
|
|
|
An example of 'train' looks as follows. |
|
``` |
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This example was too long and was cropped: |
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|
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{ |
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"bias": 3, |
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"hyperpartisan": false, |
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"published_at": "2020-01-01", |
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"text": "\"<p>This is a sample article which will contain lots of text</p>\\n \\n<p>Phasellus bibendum porta nunc, id venenatis tortor fi...", |
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"title": "Example article 4", |
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"url": "https://example.com/example4" |
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} |
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``` |
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|
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### Data Fields |
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|
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The data fields are the same among all splits. |
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|
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#### byarticle |
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- `text`: a `string` feature. |
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- `title`: a `string` feature. |
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- `hyperpartisan`: a `bool` feature. |
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- `url`: a `string` feature. |
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- `published_at`: a `string` feature. |
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|
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#### bypublisher |
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- `text`: a `string` feature. |
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- `title`: a `string` feature. |
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- `hyperpartisan`: a `bool` feature. |
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- `url`: a `string` feature. |
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- `published_at`: a `string` feature. |
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- `bias`: a classification label, with possible values including `right` (0), `right-center` (1), `least` (2), `left-center` (3), `left` (4). |
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|
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### Data Splits |
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|
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#### byarticle |
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|
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| |train| |
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|---------|----:| |
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|byarticle| 645| |
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|
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#### bypublisher |
|
|
|
| |train |validation| |
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|-----------|-----:|---------:| |
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|bypublisher|600000| 150000| |
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|
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## Dataset Creation |
|
|
|
### Curation Rationale |
|
|
|
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
|
|
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### Source Data |
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|
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#### Initial Data Collection and Normalization |
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|
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
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|
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#### Who are the source language producers? |
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|
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
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|
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### Annotations |
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|
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#### Annotation process |
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|
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
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|
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#### Who are the annotators? |
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|
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
|
|
|
### Personal and Sensitive Information |
|
|
|
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
|
|
|
## Considerations for Using the Data |
|
|
|
### Social Impact of Dataset |
|
|
|
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
|
|
|
### Discussion of Biases |
|
|
|
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
|
|
|
### Other Known Limitations |
|
|
|
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
|
|
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## Additional Information |
|
|
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### Dataset Curators |
|
|
|
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
|
|
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### Licensing Information |
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|
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The collection (including labels) are licensed under a [Creative Commons Attribution 4.0 International License](http://creativecommons.org/licenses/by/4.0/). |
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|
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### Citation Information |
|
|
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``` |
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@article{kiesel2019data, |
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title={Data for pan at semeval 2019 task 4: Hyperpartisan news detection}, |
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author={Kiesel, Johannes and Mestre, Maria and Shukla, Rishabh and Vincent, Emmanuel and Corney, David and Adineh, Payam and Stein, Benno and Potthast, Martin}, |
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year={2019} |
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} |
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``` |
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|
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### Contributions |
|
|
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Thanks to [@thomwolf](https://github.com/thomwolf), [@ghomasHudson](https://github.com/ghomasHudson) for adding this dataset. |
