README.md

metadata

annotations_creators:
  - crowdsourced
  - expert-generated
language_creators:
  - found
language:
  - en
license:
  - cc-by-4.0
multilinguality:
  - monolingual
size_categories:
  - 1M<n<10M
source_datasets:
  - original
task_categories:
  - text-classification
task_ids: []
pretty_name: HyperpartisanNewsDetection
tags:
  - bias-classification
dataset_info:
  - config_name: byarticle
    features:
      - name: text
        dtype: string
      - name: title
        dtype: string
      - name: hyperpartisan
        dtype: bool
      - name: url
        dtype: string
      - name: published_at
        dtype: string
    splits:
      - name: train
        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
        dtype:
          class_label:
            names:
              '0': right
              '1': right-center
              '2': least
              '3': left-center
              '4': left
    splits:
      - name: train
        num_bytes: 2805711609
        num_examples: 600000
      - name: validation
        num_bytes: 2805711609
        num_examples: 600000
    download_size: 1003195420
    dataset_size: 5611423218

Dataset Card for "hyperpartisan_news_detection"

Table of Contents

• Dataset Description
  • Dataset Summary
  • Supported Tasks and Leaderboards
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits
• Dataset Creation
  • Curation Rationale
  • Source Data
  • Annotations
  • Personal and Sensitive Information
• Considerations for Using the Data
  • Social Impact of Dataset
  • Discussion of Biases
  • Other Known Limitations
• Additional Information
  • Dataset Curators
  • Licensing Information
  • Citation Information
  • Contributions

Dataset Description

• Homepage: https://pan.webis.de/semeval19/semeval19-web/
• Repository: https://github.com/pan-webis-de/pan-code/tree/master/semeval19
• Paper: More Information Needed
• Point of Contact: More Information Needed
• Size of downloaded dataset files: 1.00 GB
• Size of the generated dataset: 5.61 GB
• Total amount of disk used: 6.62 GB

Dataset Summary

Hyperpartisan News Detection was a dataset created for PAN @ SemEval 2019 Task 4. 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.

There are 2 parts:

• byarticle: Labeled through crowdsourcing on an article basis. The data contains only articles for which a consensus among the crowdsourcing workers existed.
• bypublisher: Labeled by the overall bias of the publisher as provided by BuzzFeed journalists or MediaBiasFactCheck.com.

Supported Tasks and Leaderboards

More Information Needed

Languages

More Information Needed

Dataset Structure

Data Instances

byarticle

• Size of downloaded dataset files: 1.00 MB
• Size of the generated dataset: 2.80 MB
• Total amount of disk used: 3.81 MB

An example of 'train' looks as follows.

This example was too long and was cropped:

{
    "hyperpartisan": true,
    "published_at": "2020-01-01",
    "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...",
    "title": "Example article 1",
    "url": "http://www.example.com/example1"
}

bypublisher

• Size of downloaded dataset files: 1.00 GB
• Size of the generated dataset: 5.61 GB
• Total amount of disk used: 6.61 GB

An example of 'train' looks as follows.

This example was too long and was cropped:

{
    "bias": 3,
    "hyperpartisan": false,
    "published_at": "2020-01-01",
    "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...",
    "title": "Example article 4",
    "url": "https://example.com/example4"
}

Data Fields

The data fields are the same among all splits.

byarticle

• text: a string feature.
• title: a string feature.
• hyperpartisan: a bool feature.
• url: a string feature.
• published_at: a string feature.

bypublisher

• text: a string feature.
• title: a string feature.
• hyperpartisan: a bool feature.
• url: a string feature.
• published_at: a string feature.
• bias: a classification label, with possible values including right (0), right-center (1), least (2), left-center (3), left (4).

Data Splits

byarticle

	train
byarticle	645

bypublisher

	train	validation
bypublisher	600000	600000

Dataset Creation

Curation Rationale

More Information Needed

Source Data

Initial Data Collection and Normalization

More Information Needed

Who are the source language producers?

More Information Needed

Annotations

Annotation process

More Information Needed

Who are the annotators?

More Information Needed

Personal and Sensitive Information

More Information Needed

Considerations for Using the Data

Social Impact of Dataset

More Information Needed

Discussion of Biases

More Information Needed

Other Known Limitations

More Information Needed

Additional Information

Dataset Curators

More Information Needed

Licensing Information

The collection (including labels) are licensed under a Creative Commons Attribution 4.0 International License.

Citation Information

@article{kiesel2019data,
  title={Data for pan at semeval 2019 task 4: Hyperpartisan news detection},
  author={Kiesel, Johannes and Mestre, Maria and Shukla, Rishabh and Vincent, Emmanuel and Corney, David and Adineh, Payam and Stein, Benno and Potthast, Martin},
  year={2019}
}

Contributions

Thanks to @thomwolf, @ghomasHudson for adding this dataset.