| --- |
| pretty_name: BeliefSim |
| language: |
| - en |
| task_categories: |
| - text-classification |
| - tabular-classification |
| tags: |
| - misinformation |
| - belief-modeling |
| - survey-data |
| - demographic-analysis |
| license: other |
| --- |
| |
| # BeliefSim Dataset Release |
|
|
| This folder contains an anonymized, Hugging Face-ready data package for **BeliefSim: Towards Belief-Driven Simulation of Demographic Misinformation Susceptibility**. |
|
|
| ## Content Note |
|
|
| This dataset studies real misinformation and rumor examples. Some claims may contain offensive, stigmatizing, or otherwise harmful wording. Examples are included for research transparency and should be handled with care. |
|
|
| ## Files |
|
|
| - `data/claims.csv`: claim text from PANDORA and MIST-1, with source labels and gold labels where available. |
| - `data/judgments.csv`: anonymized participant-level claim judgments. |
| - `data/evaluation_instances.csv`: target claim judgments paired with two same-participant observed belief judgments. |
| - `data/wvs_group_priors.csv`: WVS-derived group belief distributions by demographic axis. |
| - `data/dataset_summary.json`: generated counts and privacy notes. |
| - `scripts/prepare_release.py`: reproducible script used to regenerate the release files from local raw sources. |
|
|
| ## Current Generated Counts |
|
|
| - Claims: 156 total, including 56 PANDORA and 100 MIST-1 claims. |
| - Judgments: 40,964 total, including 64 PANDORA and 40,900 MIST-1 judgments. |
| - Evaluation instances: 40,135 total, including 53 PANDORA and 40,082 MIST-1 instances. |
| - WVS group prior rows: 976. |
|
|
| These counts are generated from the local files available in this workspace at preparation time. |
|
|
| ## Anonymization |
|
|
| The release script removes direct identifiers and sensitive survey metadata before writing the public CSV files. In particular, it drops response IDs, Prolific IDs, IP addresses, latitude/longitude, raw timestamps, and free-text notes/comments. Participant identifiers are replaced with deterministic salted SHA-256 hashes. Demographic fields are kept only as broad categories such as gender, age group, education bucket, and living-area group where available. |
|
|
| Before public upload, verify that the upstream PANDORA, MIST-1, and WVS data-use terms permit redistribution of the fields included here. If redistribution is not permitted for any source, upload only the scripts/metadata and provide instructions for authorized users to reconstruct the dataset locally. |
|
|
| ## Loading |
|
|
| ```python |
| from datasets import load_dataset |
| |
| claims = load_dataset("MichiganNLP/beliefsim", data_files="data/claims.csv") |
| judgments = load_dataset("MichiganNLP/beliefsim", data_files="data/judgments.csv") |
| instances = load_dataset("MichiganNLP/beliefsim", data_files="data/evaluation_instances.csv") |
| wvs_priors = load_dataset("MichiganNLP/beliefsim", data_files="data/wvs_group_priors.csv") |
| ``` |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{borah2026belief, |
| title={Belief-Sim: Towards Belief-Driven Simulation of Demographic Misinformation Susceptibility}, |
| author={Borah, Angana and Khan, Zohaib and Mihalcea, Rada and P{\'e}rez-Rosas, Ver{\'o}nica}, |
| journal={arXiv preprint arXiv:2603.03585}, |
| year={2026} |
| } |
| ``` |
|
|
| Questions or collaboration inquiries about misinformation research can be directed to anganab@umich.edu. |
|
|
