--- 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= 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.