--- pretty_name: PluRule language: - en multilinguality: - multilingual task_categories: - text-classification - image-text-to-text tags: - reddit - moderation - multimodal - rule-violations license: mit viewer: false --- # 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`](https://github.com/osome-iu/PluRule). ## Citation ```bibtex @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

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 ```text 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

Cluster landscape

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

## Benchmark Results

GPT-5.2 high forest plot

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

## Hydrate Conda: ```bash conda env create -f environment-hydrate.yml conda activate plurule-hydrate ``` Without conda: ```bash 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: ```bash python hydrate/0_download.py python hydrate/1_hydrate_dataset.py python hydrate/2_download_media.py # optional ``` After hydration, the reconstructed files are: ```text 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`](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`](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.