Reddit Comment Scraper

Extract comments and replies from Reddit posts with full conversation threads preserved.

🎯 What does this actor do?

This actor scrapes comments from Reddit posts, capturing:

• All comments and nested replies in a tree structure
• Comment text, author, timestamp, and depth level
• Complete conversation threads with parent-child relationships
• Support for both top-level comments only or full reply chains

Perfect for:

• Market Research - Analyze customer opinions and feedback
• Sentiment Analysis - Understand community reactions
• Content Analysis - Study discussion patterns and trends
• Community Monitoring - Track conversations about your brand

📥 Input

Field	Type	Required	Default	Description
postUrls	Array	Yes	-	List of Reddit post URLs to scrape
maxComments	Number	No	500	Maximum number of comments to collect
includeReplies	Boolean	No	true	Whether to include nested replies
sortBy	String	No	"top"	Comment sort order (top, new, best, controversial)
maxConcurrency	Number	No	2	Maximum number of posts processed at the same time

Example Input

{
  "postUrls": [
    "https://www.reddit.com/r/technology/comments/example/discussion_thread/"
  ],
  "maxComments": 100,
  "includeReplies": true,
  "sortBy": "top",
  "maxConcurrency": 2
}

Monetization

This Actor supports Apify pay-per-event pricing. Configure a PPE event named comment in Apify Console; the Actor charges that event once for each comment row successfully written to the default dataset. The code also respects the user's maximum run cost and gracefully finishes the crawler when the SDK reports that the comment event can no longer be charged.

Do not also enable the synthetic default dataset item event for this Actor unless you intentionally want to charge dataset rows separately from the comment event.

Use with n8n

This Actor is ready to be used inside n8n automations through the official Apify integration. This is the recommended path because it works with n8n's accepted Apify node instead of requiring a dedicated wrapper node.

1. Trigger an n8n workflow from a schedule, webhook, form, or manual run.
2. Add the official Apify node, install @apify/n8n-nodes-apify if needed, and select Run an Actor and Get Dataset.
3. Set Actor ID to Newbs/reddit-comment-scraper.
4. Paste the Actor input JSON with Reddit post URLs and comment limits.
5. Send the returned comment rows to Google Sheets, Slack, Notion, Airtable, HubSpot, or an AI node.

This repository includes n8n integration assets:

• integrations/n8n-workflows - importable starter workflows that use the official Apify node.
• docs/N8N_INTEGRATION.md - official Apify-node setup, positioning, and monetization flow.
• docs/APIFY_STORE_N8N_SECTION.md - copy that can be pasted into the Apify Store Actor description.
• docs/N8N_DISTRIBUTION_KIT.md - ready-to-post community, social, and template submission copy.
• integrations/n8n-node - an optional self-hosted shortcut wrapper. It is not the primary n8n path because n8n declined verified listing for wrappers around Apify Actors.

The n8n workflow templates do not contain the scraping code. They call this Actor on Apify with the user's Apify credential, then process the dataset rows inside n8n. Billing still happens through Apify pay-per-event pricing.

Public n8n resources:

• Official Apify node package: @apify/n8n-nodes-apify
• Apify n8n docs: https://docs.apify.com/platform/integrations/n8n
• Public workflow examples: Newbs workflow examples
• Local workflow source: integrations/n8n-workflows
• Optional self-hosted wrapper: n8n-nodes-reddit-comment-scraper

Ready-to-import n8n workflow examples:

• Reddit comments clean export
• Reddit pain-point keyword scoring
• Reddit thread metrics
• Reddit AI research brief
• Reddit brand monitor for Slack
• Reddit competitor research for Google Sheets

Official Apify node input example:

{
  "postUrls": [
    "https://www.reddit.com/r/AskReddit/comments/ovihp9/what_city_would_you_never_ever_ever_live_in/"
  ],
  "maxComments": 100,
  "includeReplies": true,
  "sortBy": "top",
  "maxConcurrency": 2,
  "proxy": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"],
    "apifyProxyCountry": "US"
  }
}

Use with Make, Zapier, Pipedream, and AI agents

This Actor can also be used in other automation and agent platforms. The public templates and setup assets are maintained in a separate repository so customers can use them without exposing the private Actor source code.

Distribution assets:

• Make.com scenario templates: Newbs Make templates
• Zapier template specs and Webhooks fallback: Newbs Zapier templates
• Pipedream workflow components: Newbs Pipedream components
• GPT Actions and MCP server examples: Newbs AI agent examples
• Full distribution plan: Newbs distribution plan

Recommended customer path:

1. Pick the template for n8n, Make, Zapier, Pipedream, or an AI agent.
2. Add an Apify API token or Apify platform connection.
3. Set Actor ID to Newbs/reddit-comment-scraper.
4. Start with maxComments between 1 and 10 for the first paid test run.
5. Send the returned comment rows to Google Sheets, Slack, Airtable, Notion, HubSpot, or an AI summary step.

These templates all call this Actor through Apify. They do not include scraping logic, credentials, or private implementation code.

📤 Output

The actor outputs one row per comment for clean Excel/CSV exports. Each comment (including replies) becomes a separate row with full context.

Output Format (Flattened for Easy Analysis)

Each row contains:

{
  "postUrl": "https://www.reddit.com/r/...",
  "postTitle": "Post title here",
  "postAuthor": "original_poster",
  "postScore": "1234",
  "subreddit": "technology",

  "commentDepth": 0,
  "commentAuthor": "user1",
  "commentText": "This is the comment text",
  "commentTimestamp": "2024-01-15T10:30:00Z",
  "commentId": "abc123",

  "commentPath": "0",
  "parentPath": null,
  "isTopLevel": true,
  "replyCount": 3,

  "scrapedAt": "2024-01-15T12:00:00Z"
}

Output Fields Explained

Post Context (same for all comments from a post):

• postUrl - URL of the Reddit post
• postTitle - Title of the post
• postAuthor - Original post author
• subreddit - Subreddit name

Comment Details:

• commentDepth - Nesting level (0 = top-level, 1 = first reply, etc.)
• commentAuthor - Username of comment author
• commentText - The actual comment content
• commentTimestamp - When the comment was posted
• commentId - Reddit's comment ID

Threading Information:

• commentPath - Path showing position in thread (e.g., "0/2/1" = first comment → third reply → second sub-reply)
• parentPath - Path to parent comment (null for top-level)
• isTopLevel - Boolean indicating if it's a main comment
• replyCount - Number of direct replies to this comment

Example: How Threading Works

If a post has this structure:

Comment A (path: "0")
  └── Reply B (path: "0/0")
      └── Reply C (path: "0/0/0")
Comment D (path: "1")
  └── Reply E (path: "1/0")

You'll get 5 rows in your export:

1. Row for Comment A with commentPath: "0", parentPath: null
2. Row for Reply B with commentPath: "0/0", parentPath: "0"
3. Row for Reply C with commentPath: "0/0/0", parentPath: "0/0"
4. Row for Comment D with commentPath: "1", parentPath: null
5. Row for Reply E with commentPath: "1/0", parentPath: "1"

Benefits of This Format

✅ Excel/CSV Ready - Each comment is a row, no nested JSON columns ✅ Easy Filtering - Filter by depth, author, or isTopLevel ✅ Preserved Threading - Use commentPath/parentPath to reconstruct conversations ✅ Analysis Friendly - Count comments per author, average reply depth, etc.

🚀 How to Use

Via Apify Console

1. Add Reddit post URLs to the postUrls array
2. Set maxComments to limit data collection (useful for large threads)
3. Toggle includeReplies based on your needs:
   • true - Get full conversation threads
   • false - Get only top-level comments
4. Choose sortBy to control comment ordering
5. Click "Run" to start scraping

Via API

const input = {
  postUrls: [
    "https://www.reddit.com/r/AskReddit/comments/xyz/what_is_your_opinion/",
  ],
  maxComments: 200,
  includeReplies: true,
  sortBy: "best",
};

// Run via Apify API
const run = await client
  .actor("your-username/reddit-comment-scraper")
  .call(input);

Processing Multiple Posts

You can scrape multiple posts in one run:

{
  "postUrls": [
    "https://www.reddit.com/r/technology/comments/post1/",
    "https://www.reddit.com/r/science/comments/post2/",
    "https://www.reddit.com/r/gaming/comments/post3/"
  ],
  "maxComments": 100
}

💡 Use Cases

Market Research

Analyze product discussions and customer feedback:

• Track mentions of your brand
• Understand customer pain points
• Identify feature requests

Sentiment Analysis

Study community reactions:

• Measure response to announcements
• Track opinion trends over time
• Identify influential commenters

Content Strategy

Understand what resonates:

• Find popular discussion topics
• Identify content gaps
• Study engagement patterns

⚠️ Limitations

• Works with new Reddit interface (reddit.com)
• Respects Reddit's rate limits
• Some very deeply nested threads may require clicking "Continue thread" links
• Deleted/removed comments are skipped
• Maximum runtime: 60 minutes per run

🔧 Advanced Features

Comment Filtering

• Set includeReplies: false to get only top-level comments
• Use maxComments to limit data collection
• Comments are sorted according to sortBy parameter

Data Structure

• Nested reply structure preserves conversation context
• Each comment includes depth level for easy filtering
• Timestamps allow temporal analysis

📊 Example Analysis

With the scraped data, you can:

• Count replies per comment to find most engaging topics
• Analyze comment depth to understand conversation complexity
• Track author participation across threads
• Build word clouds from comment text
• Perform sentiment analysis on discussions

🆘 Support

Having issues? Check these common solutions:

1. No comments found - Verify the Reddit post URL is correct and public
2. Timeout errors - Reduce maxComments for very large threads
3. Missing replies - Ensure includeReplies is set to true

For additional support, please open an issue or contact support.

📝 Changelog

Version 1.0.0

• Initial release with Shreddit (new Reddit) support
• Full comment tree structure with nested replies
• Configurable comment limits and sorting
• Support for multiple posts in single run