ssingh22/reddit-activity

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 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

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/ (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:

@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:

@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.