README.md

---
pretty_name: Reddit Subreddit Activity & Retention (Responsible Reddit Research)
license: other
license_name: research-only
license_link: LICENSE
language:
- en
tags:
- reddit
- social-science
- responsible-ai
- data-filtering
- subreddit
task_categories:
- text-classification
size_categories:
- 100K<n<1M
configs:
- config_name: default
  data_files:
  - split: train
    path: data/activity_index.parquet
---

# Reddit Subreddit Activity & Retention

*Per-subreddit activity statistics — comment/post volume, distinct authors, and
subscriber count — with a locked retention-gate decision, for 369,646
non-NSFW subreddits observed in the 2025-06 and 2026-06 Reddit post archives.*

This dataset is released as part of the **Accelerating Social Science with Agents
and Responsible Research Using Reddit** initiative (see the companion
[`ssingh22/reddit-subreddit-nsfw-classification`](https://huggingface.co/datasets/ssingh22/reddit-subreddit-nsfw-classification)
dataset). Building a study corpus from raw Reddit archives requires knowing
*which subreddits actually have enough real, non-bot conversation* to be worth
including — this dataset makes that decision reproducible and citable, instead
of an ad-hoc per-project heuristic.

**Reference window:** activity is aggregated from the **2025-06** and **2026-06**
monthly post/comment archives (a 2-month proxy for a longer analysis window, not
a full-year scan — see Methodology). NSFW-dropped subreddits (per the companion
NSFW dataset) are excluded entirely; every subreddit here already passed that
filter.

## Dataset structure

One row per subreddit encountered (after NSFW/non-public/bot/deleted record-level
drops — see Methodology).

| field | type | description |
|---|---|---|
| `subreddit` | string | Subreddit name. |
| `clean_comments` | int | Comments surviving record-level drops, summed over the 2 reference months. |
| `distinct_authors` | int | Distinct commenting authors, summed over the 2 reference months — **capped at 256** (only the `>= 50` gate matters; exact above the cap is not tracked). |
| `clean_posts` | int | Submissions surviving record-level drops, summed over the 2 reference months. |
| `subscribers` | int | Subscriber count from the 2025-01 metadata crawl. |
| `retained` | bool | Whether the subreddit passes **all** retention gates below. |

### Loading

```python
from datasets import load_dataset

ds = load_dataset("ssingh22/reddit-activity", split="train")
retained = [r["subreddit"] for r in ds if r["retained"]]
```

## Methodology

**Record-level drops applied before counting** (same as the main corpus-cleaning
pipeline): subreddit in the NSFW drop-set -> drop; `subreddit_type != "public"`
-> drop; comment `body` / post `selftext` in `{[deleted],[removed],""}` -> drop;
author in the bot blocklist -> drop; comments on a thread whose post was
NSFW-flagged (in a non-rescued sub) or removed -> drop.

**Retention gate** (a subreddit is `retained` iff **all** hold):

| gate | threshold | catches |
|---|---|---|
| `clean_comments` | >= 1,000 | dead subs (no conversation) |
| `distinct_authors` | >= 50 | single-operator / bot-inflated subs |
| `clean_posts` | >= 50 | subs with no real posting activity |
| `subscribers` | >= 200 | abandoned micro-subs |

**Scope note:** thresholds were calibrated for a full multi-month window; here
they're applied to a **2-month proxy** (2025-06 + 2026-06 combined, not scaled
down) as a deliberate approximation — a coarser cut than a full-window pass
would give, but far cheaper to compute. `distinct_authors` is capped at 256
during counting purely to bound memory (the gate only needs to know whether a
sub reached 50, not the exact count above it).

See [DatasetDiscovery `scripts/filtering/`](https://github.com/someshsingh22/DatasetDiscovery)
(`build_subreddit_meta.py`, `build_activity_index.py`, `publish_activity_dataset.py`)
for the reproducing code and `docs/dataset_rebuild.md` §3.3/§7.3/§7.6 for the
full writeup, including the empirical basis for each threshold.

## Statistics

- Subreddits scanned (post-NSFW-drop, non-empty activity): **369,646**
- Retained: **22,819** (6.2%)

## Intended uses

- **Corpus cleaning.** Filter `retained == True` before building a study corpus
  from Reddit archives, alongside the companion NSFW dataset.
- **Preregistered experiments.** Cite a fixed, reproducible activity/retention
  decision instead of an ad-hoc per-project heuristic.
- **Agentic research.** Autonomous research agents can consume this as a
  ready-made signal of which communities have enough real activity to study.

## Limitations and biases

- **2-month proxy, not a full-window scan.** A subreddit active mainly outside
  2025-06/2026-06 (seasonal communities, subs that grew later) may be
  under-counted here.
- **`distinct_authors` is capped at 256** during counting — exact counts above
  that are not available, only the `>= 50` boolean.
- **Doesn't distinguish real users from harder-to-detect bots** beyond the fixed
  blocklist and structural drops (deleted/removed content, non-public subs).

## License

**Research-only.** Same terms as the companion NSFW dataset — see `LICENSE`.
Contains only subreddit-level aggregate statistics (no post text or personal
data).

## Citation

If you use this **activity / retention list**, please cite:

```bibtex
@article{si2026zipp,
  title={ZIPP: Zero-shot Image Personalization from Personas},
  author={SI, Harini and Singh, Somesh and Singla, Yaman Kumar and Doermann, David and Shah, Rajiv Ratn},
  journal={arXiv preprint arXiv:2606.08841},
  year={2026}
}
```

If you also use the companion **NSFW subreddit classification**, please cite:

```bibtex
@article{gupta2026accelerating,
  title={Accelerating Social Science Research via Agentic Hypothesization and Experimentation},
  author={Gupta, Jishu Sen and SI, Harini and Singh, Somesh Kumar and Tawseeq, Syed Mohamad and Singla, Yaman Kumar and Doermann, David and Shah, Rajiv Ratn and Krishnamurthy, Balaji},
  journal={arXiv preprint arXiv:2602.07983},
  year={2026}
}
```

## Acknowledgements

Part of the **Accelerating Social Science with Agents and Responsible Research
Using Reddit** initiative. More datasets will be released under this listing.