This dataset contains pseudonymized but re-identifiable social-media content about substance use. Access is reviewed manually and granted only for public-health / harm-reduction research. Requests without a verifiable institutional affiliation and a specific research purpose will be declined.

DATA USE AGREEMENT — read in full before requesting access.

This corpus contains Reddit posts and comments about drug use, including opioids. Author usernames are replaced by salted HMAC pseudonyms, but the dataset retains original Reddit post/comment identifiers (id, link_id, parent_id). Those identifiers can be resolved on reddit.com to the original content and, where not deleted, to the author's real account. Treat every record as identifiable personal data concerning health and potentially criminal conduct.

By requesting access you represent that you have read this agreement and agree to be bound by it.

1. Permitted use. Aggregate public-health, harm-reduction, epidemiological, computational-social-science or NLP research, conducted under the oversight of an IRB / research ethics committee (or a documented determination that such oversight is not required in your jurisdiction).

2. Prohibited uses. You will NOT: (a) attempt to re-identify, deanonymize, unmask or determine the real-world identity of any individual, including by resolving retained Reddit identifiers, cross-referencing external data, or querying any API or web service with dataset content; (b) contact, message, survey, recruit, profile, monitor or surveil any individual represented in the data; (c) use the data for law-enforcement, prosecutorial, immigration, insurance, credit, employment or any other adverse determination about an individual; (d) use it for commercial purposes, advertising, or targeting; (e) use it to facilitate the acquisition or distribution of controlled substances; (f) publish, present or otherwise disclose any verbatim quotation, username, pseudonymous user_id, Reddit identifier, or any other detail that could reasonably permit identification of an individual.

3. No redistribution. You will not republish, mirror, share, sublicense, post to any public repository or model hub, or otherwise transfer the data or any substantial derivative of it, in whole or in part, to any third party. Access is personal to you. Collaborators must request access individually. Models trained on this data must not be released if they can reproduce identifying content.

4. Security. You will store the data on access-controlled systems, restrict access to named personnel covered by this agreement, and not upload it to third-party services (including commercial LLM APIs) that may retain, train on, or disclose it.

5. Underlying rights. Content remains the intellectual property of its original authors and is subject to the Reddit User Agreement. This dataset is a research derivative; nothing here grants you rights in the underlying content. You are responsible for your own compliance with Reddit's terms and with all applicable law, including GDPR, HIPAA and equivalents.

6. Deletion. You will delete all copies upon completion of the stated research, upon withdrawal of access, or on request of the maintainers.

7. Incident reporting. You will report any accidental disclosure, re-identification, breach, or loss of control of the data to the maintainer within 72 hours.

8. Publication. Report results in aggregate. Paraphrase rather than quote. Cite the dataset and the upstream arctic_shift project.

9. Termination. Access may be revoked at any time, with or without cause. Breach terminates your rights immediately and obliges you to delete all copies.

10. No warranty. Provided "as is", without warranty of any kind. The maintainers accept no liability arising from your use. The data is a non-representative convenience sample and must not be used for clinical, diagnostic, or individual decision-making purposes.
11. Images — additional restrictions. This dataset contains photographs posted by Reddit users. Images can identify a person in ways text cannot: a face, a tattoo, a hand, a recognisable room, a prescription label, a street view. In addition to the terms above you will NOT: (a) run face detection, face recognition, biometric extraction, or any person-matching or clustering technique intended to group images by depicted individual; (b) attempt to read, enhance, or reconstruct any text visible in an image that identifies a person, address, prescription, or account; (c) perform reverse-image search on any image, or submit any image to a third-party service that performs one; (d) reproduce any image, crop, or thumbnail in a publication, presentation, poster, or model card. Report image findings only in aggregate.

12. Image provenance and integrity. Images were retrieved from the URLs recorded in the posts, not from Reddit's API. Some were deleted or replaced by the host before retrieval; such records are marked in image_status and carry no image bytes. EXIF and other embedded metadata are stripped on ingest, but you must not treat that as a guarantee that no identifying information remains inside the visible frame.

OP-Reddit-Image

A full mirror of OP-R1/OP-Reddit-Post — all 46,934,806 rows — with the post's image attached where it could still be retrieved.

Mirroring rather than shipping images alone costs ~7 GB of text on top of the images, and means you never have to join two separately gated datasets to put a post's text next to its picture.

Scale


rows (identical to OP-Reddit-Post)	46,934,806
posts flagged `has_image`	656,932
images retrieved	366,784
total size	~353 GB
shards	274, partitioned by subreddit

Retrieval outcomes

Every flagged post was attempted exactly once. Rows whose image could not be retrieved are kept, with image_status recording why — a missing image is itself a signal, and dropping those rows would bias the corpus toward newer, better-preserved content.

`image_status`	rows	meaning
`no_image`	46,277,880	not an image post (comments, text posts)
`ok`	366,784	image retrieved and stored
`404`	272,241	host no longer has it — deleted
`skipped_album`	8,978	imgur album; needs the Imgur API, not fetched
`placeholder`	3,703	host returned a stand-in image, not the original
`unsupported_host`	2,630	host outside the fetch scope (giphy, discord, …)
`removed_page`	2,442	host served an HTML removal page instead of an image
`not_an_image`	141	URL resolved to video (gifv/mp4)
`error`	7	genuine fetch failure

41.4% of flagged images were already gone. That is the single most important number here for anyone reasoning about coverage: this is a salvage of what survived, not a complete record of what was posted.

placeholder and removed_page deserve attention. imgur answers a request for a deleted image with HTTP 200 — sometimes a 503-byte PNG, sometimes an HTML page. A naive fetcher records both as successes. They are detected here by content hash and by response type, and are never stored as if they were real images.

By host, of what was retrieved: i.redd.it 335,614 and imgur 31,170.

Columns

Every column from OP-Reddit-Post, plus:

Column	Type	Meaning
`image`	`large_binary`	Image bytes, EXIF-stripped. Null unless `image_status = "ok"`.
`image_status`	`string`	See the table above. Never null.
`image_sha256`	`string`	SHA-256 of the stored bytes.
`image_bytes`	`int64`	Size in bytes. Median 626,732; mean 1,030,660.
`image_mime`	`string`	`image/jpeg`, `image/png`, `image/gif`.
`image_width` / `image_height`	`int64`	Pixel dimensions.

Processing notes

EXIF is stripped losslessly. JPEG APP1/APP13/APP14 segments and PNG text chunks are removed by walking the container, without re-encoding — so the pixels are byte-identical to what the host served and no generation loss is introduced. This removes GPS coordinates, device serial numbers and capture timestamps. It does not guarantee the visible content of an image is free of identifying detail; see the access agreement.

Row order within each subreddit matches OP-Reddit-Post, which is user-contiguous, so a user's records stay adjacent here too.

Verification. Row counts match OP-Reddit-Post exactly in all 37 partitions; all 46,934,806 rows were checked against the fetch log with zero status mismatches; and 8,005 embedded images across all 37 partitions were re-hashed with zero SHA-256 mismatches, 800 of them re-decoded with zero failures.

Retrieving single images without downloading 353 GB

The repo ships retrieve_images.py plus two indexes, so a record can be pulled by ranged read instead of downloading a shard.

from huggingface_hub import hf_hub_download
import importlib.util, sys

path = hf_hub_download("OP-R1/OP-Reddit-Image", "retrieve_images.py",
                       repo_type="dataset")
spec = importlib.util.spec_from_file_location("opr1_images", path)
mod  = importlib.util.module_from_spec(spec)
sys.modules["opr1_images"] = mod       # required before exec_module: the module
spec.loader.exec_module(mod)           # defines @dataclass(slots=True) types

rec = mod.get_image("kqd030")
open("out.jpg", "wb").write(rec.image)

mod.locate("kqd030")                   # index only - no data shard is touched
mod.get_user_images("<user_id>", limit=10)

Measured against the live repo: fetching one 1.5 MB image transferred 17.1 MB in 2.7 s - 85x less than its 1.46 GB shard, and ~22,000x less than the dataset as a whole.

The indexes are sorted by lookup key, so each parquet row group's footer statistics bound the keys inside it: a lookup reads the footer, picks the single group whose range covers the key, and transfers that alone. id_index also carries image_status and image_bytes, so you can check whether an image exists, and how large it is, without touching a data shard - worth doing when 41% of entries are 404.

file	rows	purpose
`index/id_index.parquet`	46,934,806	post id to shard + row group, status, size
`index/user_index.parquet`	3,212,292	user id to shard + row-group span, image count

Ethics

Same Data Use Agreement as the text datasets, plus image-specific restrictions: no face recognition or biometric extraction, no reverse-image search, and no reproduction of any image in a publication, presentation or model card. See the access request form.

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Total file size:

378 GB