PluRule

PluRule is a multilingual, multimodal benchmark for detecting rule violations when moderating pluralistic communities on social media: 13,371 discussion instances drawn from the Pushshift archives, each pairing a rule-violating thread with a compliant thread from the same submission, labeled against the community's own rules.

This dataset repository contains the dehydrated clustered PluRule splits and the hydrate scripts needed to reconstruct comment bodies, submissions, and optional media from the Pushshift archives.

For the full construction pipeline, evaluation harness, and paper reproduction code, see the main GitHub repository: osome-iu/PluRule.

Citation

@inproceedings{plurule2025,
  title  = {{PluRule: A Benchmark for Moderating Pluralistic Communities
            on Social Media}},
  author = {Kachwala, Zoher and Truong, Bao Tran and Muralidharan, Rasika and
            Kwak, Haewoon and An, Jisun and Menczer, Filippo},
  year   = {2026},
  booktitle = {Proc. ACL},
  note   = {Forthcoming},
}

A PluRule example: GPT-5.2 (high reasoning) is given the target comment with full context — subreddit description, rules, submission, and discussion thread — and asked to pick which rule, if any, was violated.

Files

data/
├── train_dehydrated_clustered.json.zst
├── val_dehydrated_clustered.json.zst
└── test_dehydrated_clustered.json.zst

The released files contain IDs, metadata, rules, cluster labels, answer options, and [NEEDS_HYDRATION] placeholders. Reddit text and media are not redistributed directly.

At a glance

Split	Instances	Comments	Images	Subreddits / Clusters	Rules / Clusters	Languages
Train	9,155	51,968	2,077	861 / 25	1,336 / 27	9
Val	1,382	7,631	376	537 / 25	586 / 27	9
Test	2,834	13,076	1,190	1,989 / 25	2,039 / 27	9
Total	13,371	72,675	3,643	1,989 / 25	2,885 / 27	9

Every instance contains (a) a root-to-leaf discussion thread where a moderator cited a rule on the leaf comment, (b) a compliant sibling thread from the same submission, (c) the submission itself with any images, and (d) the subreddit's full rule set.

Coverage

2D UMAP of subreddits and rules, colored by HDBSCAN cluster, with distributions across subreddit and rule clusters.

Benchmark Results

Accuracy by subreddit cluster and rule cluster for GPT-5.2 high reasoning with full context.

Hydrate

Conda:

conda env create -f environment-hydrate.yml
conda activate plurule-hydrate

Without conda:

python -m venv .venv
source .venv/bin/activate
pip install -r requirements-hydrate.txt

You also need aria2c on PATH for torrent downloads.

Run from the dataset repository root:

python hydrate/0_download.py
python hydrate/1_hydrate_dataset.py
python hydrate/2_download_media.py  # optional

After hydration, the reconstructed files are:

data/train_hydrated_clustered.json.zst
data/val_hydrated_clustered.json.zst
data/test_hydrated_clustered.json.zst

For details and troubleshooting, see hydrate/README.md.

License

The released PluRule files in this repository are MIT-licensed in their dehydrated form: IDs, metadata, labels, rules, and placeholders. The hydrate scripts and supporting code are also released under the MIT License; see LICENSE.

Hydrated moderator comments, submissions, and media are not redistributed by PluRule; they are reconstructed from the publicly archived Pushshift Reddit corpus and remain bound by Reddit's terms of service.