CDL Misinfo Detection Datasets

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 75. From these, we evaluated the quality of all of the 36 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.

Data pre-processing

These scripts were designed to transform the dataformat from the original CSV file to the parquet files.

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={A Guide to Misinformation Detection Datasets},
  author={Camille Thibault, Gabrielle Peloquin-Skulski, Jacob-Junqi Tian, Florence Laflamme, Yuxiang Guan, Reihaneh Rabbany, Jean-François Godbout, Kellin Pelrine},
  journal={ArXiv},
  year={2024},
  volume={abs/2411.05060}
}