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) 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) and/or EFCSN (European FactChecking Standards Network). 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.

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

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
• For the Apache Lucene index version of FACTors: Dwaipayan Roy

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},
}