Reddit Comment Scraper — Posts, Subreddits & Keywords

Extract Reddit comments at scale. Full nested threads, rich metadata, analytics report. No API key, no browser, fits in 512 MB RAM.

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🚀 What this scraper does

Reddit's comments are gold — for market research, brand sentiment, content ideas, AI training data, social listening. But Reddit's official API is rate-limited, requires authentication, and skips half the metadata you actually want.

This actor gives you everything Reddit shows on the page — in clean structured JSON — without an API key, without spinning up a browser, and at a price that scales.

✅ Three ways to find comments — by post URL, subreddit feed, or keyword search across all of Reddit ✅ Full nested threads — every reply, every depth level, parent-child relationships preserved ✅ Rich metadata — 24 fields per comment including score, controversiality, awards, edits, deletion status, and more ✅ Built-in analytics report — community insights computed automatically and saved alongside the data ✅ Fast and lean — runs in 512 MB RAM, no headless browser, no slow Selenium-style waits

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💡 Use cases

Who	How they use it
Market researchers	Track what real users say about products, competitors, pricing
Brand managers	Monitor mentions of your brand across thousands of subreddits
Content creators	Find trending discussions, popular questions, hot takes
AI / ML teams	Build training datasets of authentic human conversations
SEO specialists	Discover what your audience actually asks and cares about
Investors	Track retail sentiment on stocks, crypto, IPOs in real time
Academics	Sociology, linguistics, political science research

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📥 Three ways to give it a target

You can mix-and-match any of these in a single run.

Mode 1 — Direct URLs

Paste any Reddit URL. The scraper figures out whether it's a post, a subreddit feed, or a search page.

{
  "startUrls": [
    { "url": "https://www.reddit.com/r/AskReddit/comments/1u003hr/" },
    { "url": "https://www.reddit.com/r/programming/" }
  ]
}

Mode 2 — Subreddit feeds

Just list the subreddit names. The actor pulls the latest posts and scrapes all their comments.

{
  "subreddits": ["AskReddit", "MachineLearning", "investing"],
  "postSort": "hot",
  "postTime": "week",
  "maxPostsPerSource": 25
}

Mode 3 — Keyword search

Search across all of Reddit, or within specific subreddits.

{
  "keywords": ["chatgpt", "claude code", "anthropic"],
  "subreddits": ["LocalLLaMA", "OpenAI"],
  "maxPostsPerSource": 10
}

If you only provide keywords without subreddits, the actor searches globally across Reddit.

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🎛️ Filters that actually work

Every filter has been tested end-to-end.

Filter	What it does
minScore	Skip low-quality comments below this upvote count
maxDepth	Limit nesting (1 = top-level only, 2 = top + one reply level, 0 = unlimited)
maxCommentsPerPost	Cap comments per post so a megathread doesn't blow your budget
excludeDeleted	Drop [deleted] and [removed] comments
includeNSFW	Opt in to NSFW subreddits (default: skipped)
commentSort	top / new / controversial / old / qa / confidence
postSort	hot / top / new / relevance / comments / controversial
postTime	hour / day / week / month / year / all

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📤 What you get back

One dataset item per comment with 24 fields:

Field	Type	Description
id	string	Reddit comment ID
postId	string	ID of the parent post
postTitle	string	Title of the parent post
postUrl	string	Full URL of the parent post
postScore	number	Score of the parent post
subreddit	string	e.g. AskReddit
subredditPrefixed	string	e.g. r/AskReddit
author	string	Reddit username
body	string	Comment text (markdown)
score	number	Net upvotes (upvotes minus downvotes)
controversiality	number	1 if Reddit flagged the comment as controversial
totalAwards	number	Awards received
depth	number	Nesting depth (0 = top-level reply to the post)
parentId	string	ID of the parent comment or post
isTopLevel	boolean	True if this is a direct reply to the post
isSubmitter	boolean	True if the author is the post's OP
isStickied	boolean	True for moderator-pinned comments
distinguished	string | null	"moderator", "admin", or null
isDeleted	boolean	True if the comment was deleted by the user or removed by moderators
postedAt	ISO date	When the comment was posted
editedAt	ISO date | null	When the comment was last edited (null if never)
scrapedAt	ISO date	When the scraper saw it
permalink	string	Direct link to the comment on Reddit
matchedKeyword	string | null	Which of your keywords matched (for keyword-search mode)

Example output

{
  "id": "oqen70z",
  "postId": "1u003hr",
  "postTitle": "What movie plot hole is so massive that it completely ruins the story?",
  "postUrl": "https://www.reddit.com/r/AskReddit/comments/1u003hr/...",
  "postScore": 1300,
  "subreddit": "AskReddit",
  "subredditPrefixed": "r/AskReddit",
  "author": "TheAmazingSealo",
  "body": "The Butterfly Effect breaks its own rules and logic...",
  "score": 3003,
  "controversiality": 0,
  "totalAwards": 0,
  "depth": 0,
  "parentId": "1u003hr",
  "isTopLevel": true,
  "isSubmitter": false,
  "isStickied": false,
  "distinguished": null,
  "isDeleted": false,
  "postedAt": "2026-06-08T07:02:55.000Z",
  "editedAt": "2026-06-08T08:10:16.000Z",
  "scrapedAt": "2026-06-08T13:21:29.916Z",
  "permalink": "https://www.reddit.com/r/AskReddit/comments/1u003hr/.../oqen70z/",
  "matchedKeyword": null
}

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📊 Bonus: analytics report

Set includeAnalytics: true (it's on by default) and the actor computes a community insights report alongside the raw data. Saved as ANALYTICS in the run's Key-Value store.

What's inside:

• 📈 Total posts and comments processed
• ⭐ Average comment score
• 🏆 Top commenters by volume and by score
• 🔥 Hottest threads (highest engagement)
• 😡 Most controversial threads
• 📊 Distribution of comments by depth, score buckets, time-of-day

Perfect for one-glance overviews and dashboards. No extra setup — just one toggle.

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⚙️ Quick start

1. Pick a target. A subreddit name, a post URL, a keyword — anything that interests you.
2. Set limits. maxPostsPerSource: 5 and maxCommentsPerPost: 100 are reasonable starting values.
3. Click Run. Results stream into the dataset as they're scraped.

That's it. No tokens to fetch, no proxies to configure (the default works), no schema to learn.

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💰 Pricing

Pay only for what you use:

Event	Price
Actor start	$0.01 per run
Comment scraped	$2.00 per 1,000 comments ($0.002 each)

Example runs:

• 100 comments → $0.21
• 500 comments → $1.01
• 5,000 comments → $10.01
• 100,000 comments → $200.01

Apify platform usage (compute, proxy, storage) is billed separately by Apify at standard platform rates. The actor runs in 512 MB RAM with no headless browser, so platform costs stay low.

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❓ FAQ

Do I need a Reddit account or API key? No. The scraper works on Reddit's public data — anything visible without logging in.

Will it get my IP banned? The actor ships configured to use Apify Residential proxies, which rotate IPs automatically. You can override with your own proxy in the input.

How fresh is the data? Real-time. The scraper reads Reddit's live data — comments posted minutes ago are already in the results.

Does it handle deleted comments? Yes. Deleted comments are flagged with isDeleted: true so you keep the tree structure intact. Opt out with excludeDeleted: true.

Can I scrape NSFW subreddits? Yes, but you have to opt in with includeNSFW: true. By default they're skipped.

What about Reddit's "load more comments" buttons? Top comments are always returned. Very deep tail threads (beyond what Reddit returns in one shot) are noted in the log but not auto-expanded by default — increase maxCommentsPerPost to pull more.

Can I run scheduled scrapes? Yes. Use Apify's built-in Schedules. Great for daily brand-mention digests or weekly sentiment snapshots.

Will old.reddit.com / new.reddit.com URLs both work? Both. Also redd.it short links and mobile .compact URLs.

Does the actor work for private subreddits? No — private subreddits require authenticated access. Public and quarantined-but-visible subs work fine.

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🛠️ Author

Maintained by brilliant_gum.

Bug reports, feature requests, custom-scrape needs → open an issue on this actor.

If this saved you time, leave a ⭐ — it helps other Reddit researchers find the tool.