license: apache-2.0
configs:
- config_name: default
data_files:
- split: train
path: train.parquet
- split: test
path: test.parquet
- split: validation
path: validation.parquet
- config_name: faviq
data_files:
- split: dev
path: faviq/train-*
- split: test
path: faviq/test-*
- split: train
path: faviq/validation-*
language:
- en
size_categories:
- 1M<n<10M
tags:
- misinformation
- text
pretty_name: Misinformation Detection Datasets
Modalities:
- Text
CDL Misinfo Detection Datasets
Dataset Description
- Homepage: https://yxguan.github.io/ComplexData-Misinfo-test1/
- Repository: https://github.com/ComplexData-MILA/misinfo-datasets
- Paper: https://arxiv.org/abs/2104.06952
- Data Processing Script: https://github.com/YXGuan/misinfo-dataset-preprocessing
Datasets Summary
Misinformation is a challenging societal issue, and mitigating solutions are difficult to create due to data deficiencies. To address this problem, we have curated the largest collection of (mis)information datasets in the literature, totaling 72. From these, we evaluated the quality of all of the 32 datasets that consist of statements or claims. If you would like to contribute a novel dataset or report any issues, please email us or visit our GitHub. Please refer to our paper for further details.
Note for Users
Please be noted that some different labels may refer to the same thing. For example USA, United States and united states. This is due to the discrepency in labeling originated from the original datasets. Further data cleaning is recommended upon usage.
Team
This dataset is made available by Complex Data Lab, a group composed of researchers from University of Montreal and McGill University. The lab is led by Dr. Reihaneh Rabbany and Dr. Jean-François Godbout
Citation Information
@article{,
title={},
author={},
journal={ArXiv},
year={2024},
volume={abs/2012.00000}
}