docs: dataset README (schema, source, heuristic)

README.md

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+# personalization-reddit
+
+Per-subreddit `(query, preferred_answer)` pairs mined from Reddit using an
+**OP-thanks-reply** heuristic: when the original poster (OP) replies to a
+comment with thanks/gratitude, that parent comment is treated as their
+preferred answer to their own question.
+
+## Source
+
+Raw post + comment dumps from the
+[arctic_shift](https://github.com/ArthurHeitmann/arctic_shift) Pushshift
+mirror, fetched per-subreddit (entire history through the fetch date) and
+extracted with the pipeline in `may_15/reddit_pipeline/` of the
+`personalization` repo.
+
+Raw NDJSON dumps are kept locally and are not redistributed here.
+
+## Files
+
+```
+extracted/
+  pairs/sub-<subreddit>.jsonl   # one (query, preferred_answer) per line
+  stats/sub-<subreddit>.json    # funnel counts per subreddit
+```
+
+Each pair file is independent — load one sub or `concatenate_datasets` to
+combine.
+
+## Record schema (`pairs/sub-*.jsonl`)
+
+| field | type | description |
+|---|---|---|
+| `user_id` | str | anonymized OP id (HMAC of Reddit username, see `anon.py`) |
+| `timestamp` | str | post creation, ISO 8601 UTC |
+| `subreddit` | str | source subreddit name |
+| `query` | str | post title, with selftext appended if present |
+| `preferred_answer` | str | body of the comment OP thanked (via parent of the thanks reply) |
+| `top_comment` | str \| null | body of the highest-scoring non-OP comment (may equal preferred) |
+| `metadata` | object | see below |
+
+`metadata` sub-object:
+
+| field | type | description |
+|---|---|---|
+| `post_id` | str | Reddit submission id |
+| `post_score` | int | submission score at fetch time |
+| `answer_comment_id` | str | comment id of the preferred answer |
+| `answer_score` | int | preferred-answer score at fetch time |
+| `answerer_anon_id` | str | anonymized author id of the preferred answer |
+| `top_comment_id` | str \| null | comment id of the top-scoring non-OP comment |
+| `top_comment_score` | int \| null | top comment score |
+| `top_comment_anon_id` | str \| null | anonymized top-comment author id |
+| `top_equals_preferred` | bool | whether the preferred answer is also the top comment |
+| `thanks_reply_id` | str | OP's thanks-reply comment id (the signal that triggered the pair) |
+| `thanks_reply_score` | int | score of OP's thanks reply |
+| `thanks_reply_text` | str | body of OP's thanks reply |
+| `thanks_reply_timestamp` | str | thanks reply creation, ISO 8601 UTC |
+
+## Heuristic — OP thanks-reply
+
+For each post that passes a question filter:
+1. Find comments whose author == OP and whose body matches a "thanks"
+   pattern (see `signals.py::is_thanks_reply`).
+2. The parent of each such reply is recorded as a candidate "preferred answer".
+3. Materialize each candidate into a pair, joining post metadata + answer body
+   + thanks-reply context.
+
+Bots and deleted/removed authors are filtered out before pair emission
+(`signals.py`, `subreddits.py::BOT_AUTHORS`).
+
+## Anonymization
+
+Reddit usernames are hashed via HMAC-SHA256 with a per-run secret salt
+(`anon.py::anon_user_id`) before being written. Post/comment ids and text
+bodies are kept verbatim — content from public Reddit threads can still be
+re-identified by searching the post id or quoting the body.
+
+## Subreddits included in this snapshot
+
+See `extracted/stats/` for the list and per-sub funnel counts
+(`rs_records_scanned`, `keep_posts`, `thanks_refs`, `pairs_emitted`, etc.).