| --- |
| 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}, |
| } |
| ```` |
