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Dataset Card for Fake News Filipino
Dataset Summary
Low-Resource Fake News Detection Corpora in Filipino. The first of its kind. Contains 3,206 expertly-labeled news samples, half of which are real and half of which are fake.
Supported Tasks and Leaderboards
[More Information Needed]
Languages
The dataset is primarily in Filipino, with the addition of some English words commonly used in Filipino vernacular.
Dataset Structure
Data Instances
Sample data:
{
"label": "0",
"article": "Sa 8-pahinang desisyon, pinaboran ng Sandiganbayan First Division ang petition for Writ of Preliminary Attachment/Garnishment na inihain ng prosekusyon laban sa mambabatas."
}
Data Fields
[More Information Needed]
Data Splits
[More Information Needed]
Dataset Creation
Fake news articles were sourced from online sites that were tagged as fake news sites by the non-profit independent media fact-checking organization Verafiles and the National Union of Journalists in the Philippines (NUJP). Real news articles were sourced from mainstream news websites in the Philippines, including Pilipino Star Ngayon, Abante, and Bandera.
Curation Rationale
We remedy the lack of a proper, curated benchmark dataset for fake news detection in Filipino by constructing and producing what we call “Fake News Filipino.”
Source Data
Initial Data Collection and Normalization
We construct the dataset by scraping our source websites, encoding all characters into UTF-8. Preprocessing was light to keep information intact: we retain capitalization and punctuation, and do not correct any misspelled words.
Who are the source language producers?
Jan Christian Blaise Cruz, Julianne Agatha Tan, and Charibeth Cheng
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
Jan Christian Cruz, Julianne Agatha Tan, and Charibeth Cheng
Licensing Information
[More Information Needed]
Citation Information
@inproceedings{cruz2020localization,
title={Localization of Fake News Detection via Multitask Transfer Learning},
author={Cruz, Jan Christian Blaise and Tan, Julianne Agatha and Cheng, Charibeth},
booktitle={Proceedings of The 12th Language Resources and Evaluation Conference},
pages={2596--2604},
year={2020}
}
Contributions
Thanks to @anaerobeth for adding this dataset.
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