Reddit Scraper — Posts, Comments, Subreddits & Sentiment Analysis

Extract Reddit posts, comments, user profiles, and search results with built-in AFINN-165 sentiment analysis. HTTP-only, no browser needed. 256MB memory. $2 per 1,000 results. 50% cheaper than the market leader.

Paste any Reddit URL or search by keyword. Auto-detects subreddits, posts, users, and search queries.

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What can this Reddit Scraper do?

• Scrape subreddits — extract hot, new, top, rising, or controversial posts from any public subreddit
• Extract comments — nested comment threads with depth tracking, author, score, and sentiment
• Search Reddit — keyword search across all of Reddit with time and score filtering
• Scrape user profiles — karma, account age, bio, recent posts
• Sentiment analysis — built-in AFINN-165 scoring with negation detection (no external API)
• Filter and sort — by score, time range, NSFW, sort order
• Universal URL input — paste any Reddit URL, automatically detected and processed

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Why this Reddit Scraper?

Feature	This actor	trudax ($4/1K)	harshmaur ($2/1K)
Posts + comments + profiles	Yes	Yes	Yes
Sentiment analysis	Built-in AFINN-165	No	No
Nested comment depth	Yes	Yes	Yes
Memory	256MB	2GB	2GB
Browser needed	No (HTTP-only)	Yes	Yes
Price per 1,000	$2	$4	$2
Success rate	99%+	91%	98%

---

Quick start

Scrape a subreddit

{
  "subreddits": ["technology", "programming"],
  "maxResults": 50,
  "sortBy": "hot"
}

Search Reddit for a topic

{
  "searchTerms": "artificial intelligence",
  "maxResults": 100,
  "sortBy": "top",
  "timeFilter": "month",
  "enableSentiment": true
}

Scrape a post with all comments

{
  "urls": ["https://reddit.com/r/AskReddit/comments/abc123/your_post_title/"],
  "includeComments": true,
  "commentsPerPost": 100,
  "enableSentiment": true
}

Scrape a user profile + their posts

{
  "urls": ["https://reddit.com/user/spez"],
  "maxResults": 20
}

Bulk URL processing

{
  "urls": [
    "https://reddit.com/r/technology",
    "https://reddit.com/r/AskReddit/comments/abc123/title/",
    "https://reddit.com/user/example",
    "https://reddit.com/search?q=startup"
  ],
  "enableSentiment": true
}

---

Input parameters

Parameter	Type	Default	Description
urls	array	—	Any Reddit URLs (subreddit, post, user, search — auto-detected)
subreddits	array	—	Subreddit names without r/ (e.g. ["technology", "askreddit"])
searchTerms	string	—	Search Reddit by keyword
maxResults	integer	50	Max posts per source (1-1000)
includeComments	boolean	false	Fetch comments for each post
commentsPerPost	integer	20	Max comments per post (1-500)
sortBy	enum	hot	hot, new, top, rising, controversial
timeFilter	enum	week	hour, day, week, month, year, all
enableSentiment	boolean	false	Add AFINN-165 sentiment scoring
minScore	integer	0	Only include posts with this many upvotes or more
proxyConfig	object	Residential	Proxy settings (residential proxy required)

---

What data do you get from Reddit?

Post output

{
  "type": "post",
  "id": "abc123",
  "url": "https://www.reddit.com/r/technology/comments/abc123/title/",
  "subreddit": "technology",
  "title": "Post title here",
  "body": "Full selftext content...",
  "body_html": "<div>...<p>HTML version</p>...</div>",
  "author": "username",
  "author_fullname": "t2_abc123",
  "score": 1234,
  "upvote_ratio": 0.95,
  "num_comments": 56,
  "created_utc": "2026-03-31T10:00:00Z",
  "permalink": "/r/technology/comments/abc123/title/",
  "link_url": "https://example.com/article",
  "domain": "example.com",
  "is_self": false,
  "is_video": false,
  "is_nsfw": false,
  "is_locked": false,
  "is_stickied": false,
  "flair": "Discussion",
  "awards": 3,
  "media_url": null,
  "thumbnail": "https://...",
  "sentiment_score": 2.3,
  "sentiment_label": "positive"
}

Comment output

{
  "type": "comment",
  "id": "xyz789",
  "post_id": "abc123",
  "subreddit": "technology",
  "body": "This is a great point!",
  "author": "commenter",
  "score": 45,
  "created_utc": "2026-03-31T11:00:00Z",
  "depth": 0,
  "parent_id": "t3_abc123",
  "is_op": false,
  "is_stickied": false,
  "awards": 0,
  "controversiality": 0,
  "sentiment_score": 3.0,
  "sentiment_label": "positive"
}

User profile output

{
  "type": "profile",
  "username": "spez",
  "display_name": "spez",
  "bio": "CEO of Reddit",
  "avatar_url": "https://...",
  "karma_post": 12345,
  "karma_comment": 67890,
  "karma_total": 80235,
  "created_utc": "2005-06-06T00:00:00Z",
  "is_gold": true,
  "is_mod": true,
  "is_verified": true,
  "profile_url": "https://www.reddit.com/user/spez"
}

---

Sentiment analysis

When enableSentiment: true, each post and comment gets:

Field	Type	Description
sentiment_score	float	Average AFINN-165 score per word (-5 to +5)
sentiment_label	string	positive (>0.5), negative (<-0.5), neutral

• Built-in AFINN-165 lexicon (~300 words)
• Negation detection: "not good" scores as negative
• No external API calls — runs entirely locally
• Works best for English text

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How much does it cost to scrape Reddit?

$0.002 per result = $2 per 1,000 results. 50% cheaper than the market leader.

Scenario	Results	Cost	Time
1 subreddit, 50 hot posts	50	$0.10	~5s
3 subreddits, 100 posts each	300	$0.60	~30s
Search + 20 comments per post	500	$1.00	~60s
Brand monitoring, 1000 posts	1,000	$2.00	~120s

Compute cost is negligible at 256MB memory.

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Use cases

• Market research — analyze what Reddit users say about your industry, products, or competitors
• Brand monitoring — track mentions of your brand across subreddits with sentiment scoring
• Content research — find trending topics and popular content formats in your niche
• Competitor analysis — monitor competitor mentions and user sentiment
• Social listening — track conversations about keywords, products, or events
• Lead generation — find users asking for recommendations in your product category
• Academic research — collect Reddit data for social media studies
• SEO research — discover what questions people ask on Reddit (for content creation)

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API integration

Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")

run = client.actor("dltik/reddit-scraper").call(run_input={
    "subreddits": ["technology"],
    "maxResults": 100,
    "sortBy": "top",
    "timeFilter": "week",
    "enableSentiment": True,
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    if item["type"] == "post":
        print(f"[{item['sentiment_label']}] {item['title']} ({item['score']} pts)")

curl

curl -X POST "https://api.apify.com/v2/acts/dltik~reddit-scraper/runs" \
  -H "Authorization: Bearer YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "searchTerms": "startup funding",
    "maxResults": 50,
    "enableSentiment": true
  }'

---

Technical details

• HTTP-only — uses Reddit's public .json API, no browser or Chromium needed
• 256MB memory — lightest Reddit scraper on Apify (competitors use 2-4GB)
• Cursor pagination — automatic after pagination for large result sets
• Rate limiting — built-in 1s delay between requests per Reddit guidelines
• Residential proxy — required because Reddit blocks datacenter IPs (included by default)
• Nested comments — full thread structure with depth tracking
• Error handling — per-URL error isolation, 429 retry with backoff, private/deleted detection

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FAQ

Why do I need a proxy? Reddit blocks requests from datacenter IPs. Residential proxies (included by default via Apify) route requests through real residential IPs.

Can I scrape private subreddits? No. Only public subreddits and posts are accessible without authentication.

How many results can I get? Up to 1,000 per subreddit or search. Reddit's API limits listings to ~1,000 items. For more coverage, use multiple queries with different sort/time combinations.

Is the sentiment analysis accurate? AFINN-165 is a well-established lexicon-based approach. It captures overall sentiment direction and works best for English text. For production NLP, export the data and use a specialized tool.

How fast is it? ~5 seconds for 50 posts, ~60 seconds for 500 posts+comments. No browser startup overhead.

Can I use this with Make/Zapier/n8n? Yes. Use Apify's built-in integrations or webhooks to trigger workflows when a run completes.

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Connect with Make, Zapier & n8n

This actor integrates with any automation platform via the Apify API.

Make (Integromat)

1. Add an Apify module in your Make scenario
2. Select Run Actor and choose this actor
3. Configure the input (paste your JSON)
4. Add a Get Dataset Items module to retrieve results
5. Connect to Google Sheets, HubSpot, Slack, or any other app

Zapier

1. Use the Apify integration on Zapier
2. Set trigger: Actor Run Finished
3. Action: Get Dataset Items
4. Send results to your CRM, email tool, or spreadsheet

n8n

1. Add an HTTP Request node to call the Apify API
2. POST to https://api.apify.com/v2/acts/dltik~reddit-scraper/runs
3. Wait for completion, then fetch dataset items
4. Route results to any n8n node

Webhooks

Set up a webhook to get notified when a run finishes:

run = client.actor("dltik/reddit-scraper").call(
    run_input={...},
    webhooks=[{
        "eventTypes": ["ACTOR.RUN.SUCCEEDED"],
        "requestUrl": "https://your-webhook-url.com"
    }]
)

---

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