Reddit Viral Scraper - Cross-Reddit Search & Post Extraction API

Extract Reddit posts from all subreddits with 40+ fields per post including title, body, author, vote counts, timestamps, engagement metrics, flair text, media URLs, subreddit metadata, and optional full comment threads with reply structure. This API searches across Reddit using advanced CloudSearch syntax with boolean operators, field-specific queries, time period filtering, and multiple sort methods — structured JSON for cross-community discovery, trend analysis, and social intelligence pipelines.

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Why Choose This Reddit Search Extraction API

40+ Fields with Comment Threads & CloudSearch Query Syntax

🔍 Advanced Search Queries Search across all subreddits using CloudSearch syntax: boolean operators (AND/OR/NOT), field-specific search (title, selftext, author, subreddit), exact phrases, and complex nested queries.

📊 40+ Data Fields Per Post Complete metadata: title, body, author, score, upvotes/downvotes, timestamps, flair, media URLs, subreddit info (name, type, subscribers), content flags, and duplicate tracking.

💬 Full Comment Thread Extraction Optional extraction of complete comment trees with reply structure, threading info (parent_id, reply_level), per-comment engagement metrics, and author data.

⏰ Flexible Filtering & Sorting Filter by time period (hour, day, week, month, year, all) and sort by relevance, hot, top, new, or comment count.

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Quick Start Guide

How to Extract Reddit Posts in 3 Steps

Step 1: Configure Parameters

Enter a search query, set sort method and time filter, configure max posts and comment extraction.

Step 2: Run the Actor

Click "Start" to begin extraction. Reddit is searched and posts with metadata are collected.

Step 3: Access Structured Results

Download JSON dataset or integrate via Apify API into your analytics pipeline.

Example Input

{
  "query": "digital marketing",
  "sort_by": "hot",
  "time_filter": "week",
  "max_posts": 1000,
  "comments": true
}

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Input Parameters

Parameter	Type	Required	Description
🔍 Query	String	Yes	Search query using CloudSearch syntax (boolean, field-specific)
📊 Sort By	String	Yes	Sort method: relevance, hot, top, new, comments
⏰ Time Filter	String	Yes	Time period: all, hour, day, week, month, year
📋 Max Posts	Number	Yes	Maximum posts to extract
💬 Comments	Boolean	Yes	Extract full comment threads

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Output Data Schema

Each extracted post returns 40+ structured fields with optional comment threads:

Post Fields

Field	Type	Description
subreddit	String	Subreddit name
subreddit_type	String	Subreddit type (public, private)
subreddit_subscribers	Integer	Subscriber count
id	String	Post unique ID
author	String	Post author username
created	String	Creation timestamp
title	String	Post title
body	String	Post text content
score	Integer	Net score (upvotes - downvotes)
upvotes	Integer	Upvote count
downvotes	Integer	Downvote count
flair_text	String	Post flair
media_url	String	Media content URL
archived	Boolean	Archived status
locked	Boolean	Locked status
over_18	Boolean	NSFW flag

Comment Fields (when comments: true)

Field	Type	Description
id	String	Comment unique ID
author	String	Comment author
body	String	Comment text
score	Integer	Comment score
parent_id	String	Parent comment ID
reply_level	Integer	Thread depth level
is_root	Boolean	Root comment flag

Example Output

{
  "processor": "https://apify.com/agentx/reddit-viral-scraper",
  "processed_at": "2025-01-15T14:23:45.123Z",
  "subreddit": "marketing",
  "subreddit_subscribers": 2800000,
  "id": "abc123",
  "author": "MarketingPro99",
  "title": "Effective digital marketing strategies for 2025",
  "body": "Here are the latest trends in digital marketing...",
  "score": 1250,
  "upvotes": 1300,
  "downvotes": 50,
  "comments": [
    {
      "id": "xyz789",
      "is_root": true,
      "author": "MarketingExpert",
      "body": "Great insights!",
      "score": 145,
      "parent_id": null,
      "reply_level": 0
    }
  ]
}

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Integration Examples

Python Integration

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")

run_input = {
    "query": "digital marketing",
    "sort_by": "hot",
    "time_filter": "week",
    "max_posts": 100,
    "comments": True
}

run = client.actor("dM1WGhL57QQWIRlJG").call(run_input=run_input)
dataset_items = client.dataset(run["defaultDatasetId"]).list_items().items

for item in dataset_items:
    print(f"r/{item['subreddit']} | {item['title'][:60]} | Score: {item['score']}")

JavaScript Integration

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_API_TOKEN' });

const input = {
  query: 'digital marketing',
  sort_by: 'hot',
  time_filter: 'week',
  max_posts: 100,
  comments: true
};

const run = await client.actor('dM1WGhL57QQWIRlJG').call(input);
const { items } = await client.dataset(run.defaultDatasetId).listItems();

items.forEach(item => {
  console.log(`r/${item.subreddit} | ${item.title.substring(0, 60)} | Score: ${item.score}`);
});

Make.com (Integromat) Integration

1. Add an Apify module to your Make scenario
2. Select Run an Actor action
3. Set Actor ID to dM1WGhL57QQWIRlJG
4. Configure input JSON with query and parameters
5. Set Run synchronously to YES
6. Add Get Dataset Items module to receive post data

N8N Integration

1. Add an Apify node to your n8n workflow
2. Set Actor to dM1WGhL57QQWIRlJG
3. Configure query and parameters in input JSON
4. Use downstream nodes to process post and comment data

JSON-LD Metadata

{
  "@context": "https://schema.org",
  "@type": "SoftwareApplication",
  "name": "Reddit Viral Scraper",
  "description": "Cross-Reddit search and post extraction API with 40+ fields, comment threads, and CloudSearch query syntax",
  "applicationCategory": "Developer Tools",
  "operatingSystem": "Cloud",
  "url": "https://apify.com/agentx/reddit-viral-scraper?fpr=aiagentapi",
  "dateModified": "2026-06-24",
  "offers": {
    "@type": "Offer",
    "price": "0.008",
    "priceCurrency": "USD"
  }
}

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Pricing & Cost Calculator

Transparent Pay-Per-Use Model

Event Type	Price	Description
Actor Start	$0.005	Per run initialization
Post	$0.008	Per post extracted with full metadata
Comment	$0.00017	Per comment extracted with threading data

Cost Examples

Posts Only (100 posts, no comments):

• Posts: 100 × $0.008 = $0.80
• Total: ~$0.81

Posts + Comments (100 posts, ~50 comments each):

• Posts: 100 × $0.008 = $0.80
• Comments: 5,000 × $0.00017 = $0.85
• Total: ~$1.66

Large Search (1,000 posts with comments):

• Posts: 1,000 × $0.008 = $8.00
• Comments: 50,000 × $0.00017 = $8.50
• Total: ~$16.51

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Use Cases & Applications

Brand & Reputation Monitoring

Brand Mention Tracking Search for brand names across all subreddits to monitor customer sentiment, identify complaints, and track discussion volume over time.

Crisis Detection Configure recurring searches to detect sudden spikes in negative mentions for early warning on reputation issues.

Market & Competitive Intelligence

Trend Discovery Monitor trending posts by sorting by "hot" across industry subreddits to identify emerging topics before they reach mainstream channels.

Competitor Analysis Track competitor product mentions, feature requests, and user complaints to inform product roadmap decisions.

Content & Research

Audience Research Analyze top-performing posts in target subreddits to understand what content resonates with specific communities.

Sentiment Analysis Pipeline Feed post and comment text into NLP pipelines for automated sentiment scoring and opinion mining at scale.

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FAQ

What query syntax is supported?

CloudSearch syntax with boolean operators (AND, OR, NOT), field-specific search (title:, selftext:, author:, subreddit:), exact phrases, and complex nested queries with parentheses.

How do comments work?

Set comments: true to extract full comment threads per post. Each comment includes author, text, score, parent_id, and reply_level for thread reconstruction.

Can I search specific subreddits?

Yes. Use subreddit:name in the query field. Combine multiple subreddits with OR: (subreddit:marketing OR subreddit:advertising).

What time filters are available?

Filter by: hour, day, week, month, year, or all (no filter). Combine with sort options for precise result targeting.

Is there a limit on results?

Set max_posts up to thousands. Processing time and cost scale with volume. Comment extraction significantly increases processing time.

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SEO Keywords & Search Terms

Primary Keywords

Reddit search API, Reddit post extraction, Reddit scraper API, Reddit comment extraction, Reddit content monitoring, Reddit data pipeline, cross-subreddit search API

Long-Tail Keywords

extract Reddit posts with comments structured JSON API, Reddit CloudSearch query post extraction pipeline, Reddit brand monitoring trend analysis API, Reddit viral post scraper 40 fields engagement scoring, Reddit cross-subreddit trend detection content intelligence, Reddit post extraction pipeline sentiment analysis marketing signals, bulk Reddit data API upvote velocity viral scoring

Industry Terms

social listening, content intelligence, sentiment analysis, trend detection, community monitoring, opinion mining, brand monitoring

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Trust & Certifications

• ✅ Enterprise Ready - Processing thousands of posts per run with 99.9% uptime
• ✅ GDPR Compliant - EU data protection standards
• ✅ 40+ Data Fields - Comprehensive post and comment intelligence
• ✅ Regular Updates - Continuous maintenance for platform changes

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Legal & Compliance

Data Rights & Usage

All data extracted by this actor originates from publicly accessible Reddit content. Users are responsible for ensuring their use complies with applicable laws and Reddit's Terms of Service.

Privacy Compliance

• GDPR: Compliant with EU General Data Protection Regulation. No personal data is stored beyond the extraction session.
• CCPA: Compliant with California Consumer Privacy Act requirements.

Platform Terms of Service

Users must review and comply with Reddit's Terms of Service regarding data usage. This tool accesses only publicly available content.

Enterprise Support

For enterprise licensing, custom integrations, or compliance inquiries:

• Telegram: @AiAgentApi

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Support & Community

• 👥 Community: @Apify_Actor
• 👤 Contact Team: @AiAgentApi

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Last Updated: June 24, 2026