Reddit Search Scraper

Search Reddit for posts, comments, or users by keyword + subreddit + time window. Returns full post metadata (title, author, score, comments count, awards, flairs, NSFW/spoiler flags, edit/created timestamps, post URL, embedded text/video/image), and optionally top comments per post.

Uses Reddit's public .json endpoint — no OAuth, no API key, no proxy needed for normal workloads.

Features

• Bulk multi-search by {query, subreddit, sort, time, type} per item
• Search across all of Reddit or restrict to a single subreddit
• All 5 sort modes: relevance, hot, top, new, comments
• All 6 time windows: hour, day, week, month, year, all
• All 3 search types: link (posts), comment, user
• Optional: fetch top N comments per post (additional request each)
• Cursor-based pagination handled automatically
• Rich post normalization including isVideo/isImage/isSelfPost flags, upvote ratio, NSFW/spoiler/stickied flags, link flair, author flair, edit timestamps

Input

{
  "searches": [
    { "query": "ai agent", "subreddit": "MachineLearning", "sort": "new", "time": "month", "type": "link" },
    { "query": "openai",   "subreddit": "",               "sort": "top",  "time": "week",  "type": "link" }
  ],
  "maxResultsPerSearch": 100,
  "fetchComments": false,
  "maxCommentsPerPost": 10
}

Field	Type	Default	Notes
searches	array	(required)	Each {query, subreddit?, sort?, time?, type?}
maxResultsPerSearch	int	100	Reddit caps at ~1000
fetchComments	bool	false	Adds 1 request per post
maxCommentsPerPost	int	10	Cap when fetchComments on

Sort + time + type

Field	Options
sort	relevance, hot, top, new, comments
time	hour, day, week, month, year, all
type	link (posts, default), comment, user

Output (one row per result)

{
  "resultType": "link",
  "id": "1abc234",
  "fullname": "t3_1abc234",
  "subreddit": "MachineLearning",
  "subredditId": "t5_2qh1i",
  "subredditSubscribers": 3450000,
  "author": "JaneAI",
  "authorFlair": "PhD Student",
  "title": "Our new AI agent paper achieves SOTA on...",
  "text": "We present a new approach...",
  "url": "https://arxiv.org/abs/2025.12345",
  "permalink": "https://www.reddit.com/r/MachineLearning/comments/1abc234/our_new_ai_agent_paper.../",
  "isSelfPost": false,
  "isVideo": false,
  "isImage": false,
  "thumbnail": "https://b.thumbs.redditmedia.com/...jpg",
  "score": 1245,
  "upvoteRatio": 0.94,
  "numComments": 187,
  "numCrossposts": 12,
  "awards": 3,
  "flair": "Research",
  "domain": "arxiv.org",
  "isNsfw": false,
  "isSpoiler": false,
  "isStickied": false,
  "createdAt": "2026-05-15T14:23:00.000Z",
  "editedAt": null,
  "comments": [
    { "id": "j1abc", "author": "...", "text": "Great work!", "score": 56, "createdAt": "...", "permalink": "...", "awards": 0 }
  ],
  "searchQuery": { "query": "ai agent", "subreddit": "MachineLearning", "sort": "new", "time": "month", "type": "link" },
  "scrapedAt": "2026-05-18T12:00:00.000Z"
}

Use cases

• Brand monitoring: track mentions of your product/company across all of Reddit
• Competitor intel: monitor what users are saying about competitors in niche subreddits
• Trend research: discover emerging topics in r/MachineLearning, r/Entrepreneur, etc.
• Content discovery: seed your newsletter / blog with top-of-week posts per topic
• Influencer research: identify high-karma users posting on specific topics (use type=user)
• Sentiment analysis pipelines: bulk-ingest posts/comments for downstream NLP
• Crisis monitoring: real-time scrape (run every 5min) for mentions of your brand + negative sentiment keywords

Notes

• No auth needed: Reddit's .json endpoint is public. Anonymous rate limit is generous for normal scraping (a few hundred requests per minute per IP).
• High-volume runs: if you scrape 1000+ posts in a tight loop you may see 429s — the actor backs off automatically. For heavy use, run with Apify residential proxy.
• Search depth limit: Reddit itself caps search at ~1000 results regardless of pagination — the actor stops automatically.
• Comments are top 10 by score — for full comment threads, use a separate dedicated Reddit comments scraper or hit <permalink>.json manually.
• Old Reddit data: for pre-2022 historical data, Pushshift dumps are more comprehensive (Reddit search ignores very old indexes).
• type=user mode returns user profiles matching the query — useful for influencer discovery in a niche.

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Changelog

• 2026-05-20 — Maintenance pass: reviewed the input schema and default values for a smooth one-click start, and rebuilt the Actor on the latest base image.

Last reviewed: 2026-05-20.