task_categories:text-classification annotations_creators:expert-generated language_creators:expert-generated multilinguality:monolingual size_categories:n<1K source_datasets:original language:en license:unknown region:us
Fake news has become a major societal issue and a technical challenge for social media companies to identify. This content is difficult to identify because the term "fake news" covers intentionally false, deceptive stories as well as factual errors, satire, and sometimes, stories that a person just does not like. Addressing the problem requires clear definitions and examples. In this work, we present a dataset of fake news and satire stories that are hand coded, verified, and, in the case of fake news, include rebutting stories. We also include a thematic content analysis of the articles, identifying major themes that include hyperbolic support or condemnation of a gure, conspiracy theories, racist themes, and discrediting of reliable sources. In addition to releasing this dataset for research use, we analyze it and show results based on language that are promising for classification purposes. Overall, our contribution of a dataset and initial analysis are designed to support future work by fake news researchers.
@inproceedings{inproceedings,
author = {Golbeck, Jennifer and Everett, Jennine and Falak, Waleed and Gieringer, Carl and Graney, Jack and Hoffman, Kelly and Huth, Lindsay and Ma, Zhenya and Jha, Mayanka and Khan, Misbah and Kori, Varsha and Mauriello, Matthew and Lewis, Elo and Mirano, George and IV, William and Mussenden, Sean and Nelson, Tammie and Mcwillie, Sean and Pant, Akshat and Cheakalos, Paul},
year = {2018},
month = {05},
pages = {17-21},
title = {Fake News vs Satire: A Dataset and Analysis},
doi = {10.1145/3201064.3201100}
}
---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- en
license:
- unknown
multilinguality:
- monolingual
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- text-classification
task_ids: []
pretty_name: Fake News English
dataset_info:
  features:
  - name: article_number
    dtype: int32
  - name: url_of_article
    dtype: string
  - name: fake_or_satire
    dtype:
      class_label:
        names:
          '0': Satire
          '1': Fake
  - name: url_of_rebutting_article
    dtype: string
  splits:
  - name: train
    num_bytes: 78078
    num_examples: 492
  download_size: 3002233
  dataset_size: 78078
---

# Dataset Card for Fake News English

## Table of Contents
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
  - [Languages](#languages)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-fields)
  - [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
  - [Curation Rationale](#curation-rationale)
  - [Source Data](#source-data)
  - [Annotations](#annotations)
  - [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
  - [Social Impact of Dataset](#social-impact-of-dataset)
  - [Discussion of Biases](#discussion-of-biases)
  - [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
  - [Dataset Curators](#dataset-curators)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)
  - [Contributions](#contributions)

## Dataset Description
- **Homepage:** https://dl.acm.org/doi/10.1145/3201064.3201100**
- **Repository:** https://github.com/jgolbeck/fakenews/
- **Paper:** https://doi.org/10.1145/3201064.3201100
- **Leaderboard:**
- **Point of Contact:** Jennifer Golbeck (http://www.jengolbeck.com)

### Dataset Summary
This dataset contains URLs of news articles classified as either fake or satire. The articles classified as fake also have the URL of a rebutting article.

### Supported Tasks and Leaderboards
[More Information Needed]

### Languages
English

## Dataset Structure

### Data Instances
```
{
"article_number": 102 ,
"url_of_article": https://newslo.com/roger-stone-blames-obama-possibility-trump-alzheimers-attacks-president-caused-severe-stress/ ,
"fake_or_satire": 1,  # Fake
"url_of_rebutting_article": https://www.snopes.com/fact-check/donald-trumps-intelligence-quotient/
}
```

### Data Fields
- article_number: An integer used as an index for each row
- url_of_article: A string which contains URL of an article to be assessed and classified as either Fake or Satire
- fake_or_satire: A classlabel for the above variable which can take two values- Fake (1) and Satire (0)
- url_of_rebutting_article: A string which contains a URL of the article used to refute the article in question (present - in url_of_article)

### Data Splits
This dataset is not split, only the train split is available.

## 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
Golbeck, Jennifer
Everett, Jennine 
Falak, Waleed
Gieringer, Carl
Graney, Jack 
Hoffman, Kelly 
Huth, Lindsay 
Ma, Zhenya 
Jha, Mayanka 
Khan, Misbah 
Kori, Varsha 
Mauriello, Matthew 
Lewis, Elo 
Mirano, George 
IV, William 
Mussenden, Sean 
Nelson, Tammie 
Mcwillie, Sean 
Pant, Akshat 
Cheakalos, Paul

### Licensing Information
[More Information Needed]

### Citation Information
@inproceedings{inproceedings,
author = {Golbeck, Jennifer and Everett, Jennine and Falak, Waleed and Gieringer, Carl and Graney, Jack and Hoffman, Kelly and Huth, Lindsay and Ma, Zhenya and Jha, Mayanka and Khan, Misbah and Kori, Varsha and Mauriello, Matthew and Lewis, Elo and Mirano, George and IV, William and Mussenden, Sean and Nelson, Tammie and Mcwillie, Sean and Pant, Akshat and Cheakalos, Paul},
year = {2018},
month = {05},
pages = {17-21},
title = {Fake News vs Satire: A Dataset and Analysis},
doi = {10.1145/3201064.3201100}
}

### Contributions

Thanks to [@MisbahKhan789](https://github.com/MisbahKhan789), [@lhoestq](https://github.com/lhoestq) for adding this dataset.