---
license: mit
task_categories:
- text-classification
language:
- en
tags:
- fact-checking
- ifcn
- claim
- misinformation
- fake-news
- disinformation
pretty_name: FACTors
size_categories:
- 100K<n<1M
---

# FACTors: A New Dataset for Studying Fact-checking Ecosystem

This includes the dataset presented in the paper titled *"FACTors: A New Dataset for Studying Fact-checking Ecosystem"* accepted for [*the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2025)*](https://sigir2025.dei.unipd.it/) as a Resource & Reproducibility paper.

*FACTors* contains 118,112 claims from 117,993 fact-checking reports in English (co-)authored by 1,953 individuals and published during the period 1995-2025 by 39 fact-checking organisations that are active signatories of the [IFCN (International Fact-Checking Network)](https://ifcncodeofprinciples.poynter.org/signatories) and/or [EFCSN (European FactChecking Standards Network)](https://members.efcsn.com/signatories). It contains 7,327 overlapping claims investigated by multiple fact-checking organisations, corresponding to 2,977 unique claims. More details are available on the GitHub [page](https://github.com/altuncu/FACTors).

# Dataset Structure

FACTors dataset is provided with a single CSV file which contains the following columns:

| Field Name | Description
| -----------|----------------
| Row ID | Primary Key
| Report ID | ID given to each unique report
| Claim ID | ID given to each unique claim
| Claim | Textual claim being fact-checked
| Content | *(not published to prevent copyright infringement)*
| Date published | Date of publication of the report in ISO 8601 format
| Author | Author(s) of the fact-checking report
| Organisation | Name of the fact-checking organisation publishing the report
| Original verdict | Conclusion of the fact-check
| Title | Heading of the report
| URL | Online link to the report
| Normalised rating | One of six predefined ratings derived from the original verdict, using a fine-tuned RoBERTa [model](https://huggingface.co/ealtuncu/verdict-normaliser-roberta)

## Contact

If you have any questions about the dataset and/or source codes, please reach out to the contributors via email:
- For more information about FACTors and its example applications provided: [Enes Altuncu](mailto:enes.altuncu@iuc.edu.tr)
- For the Apache Lucene index version of FACTors: [Dwaipayan Roy](mailto:dwaipayan.roy@iiserkol.ac.in)

## Citation

Please cite our work as follows if you use our dataset or the provided source codes in your research:

````
@inproceedings{FACTors2025,
  title={{FACTors}: A New Dataset for Studying Fact-checking Ecosystem},
  authors={Altuncu, Enes and 
           Ba\c{s}kent, Can. and 
           Bhattacherjee, Sanjay and 
           Li, Shujun and 
           Roy, Dwaipayan},
  year={2025},
  numpages={10},
  doi={10.1145/3726302.3730339},
  booktitle={Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '25), July 13--18, 2025, Padua, Italy},
  publisher={ACM},
}
````