How to Use Facebook Posts Scraper to Extract Data (2026 Guide)

What is Facebook Posts Scraper?

Extract posts, comments, reactions, and engagement data from public Facebook pages and profiles.

The Facebook Posts Scraper is a powerful tool designed for social media managers, researchers, and PR agencies to monitor the world's largest social network. It safely navigates Facebook's complex interface to extract data from any public Facebook Page or User Profile. You can seamlessly scrape historical timelines to gather the raw text of posts, embedded media links, and highly detailed engagement metrics (including specific reaction types like Love, Haha, Angry). Beyond the posts themselves, the scraper dives into the comment sections, allowing you to extract user sentiments, identify top commenters, and measure organic brand reach. This data is invaluable for competitor benchmarking, crisis management, and trend detection.

Key Features

• Scrape all posts from public Pages and User Profiles
• Extract massive volumes of user comments and replies
• Get precise counts of all Reaction types (Like, Love, Wow, etc.)
• Extract video, image, and external article URLs
• Filter extractions by strict date ranges
• Bypass Facebook login walls using Apify's residential proxies

How to Extract Data (Step by Step)

Extracting data using the Facebook Posts Scraper is incredibly straightforward. It runs entirely in the cloud, meaning you don't need to install any desktop software.

1. Click the 'Try for Free' button to access the Facebook Scraper on Apify.
2. Log in to your free Apify workspace.
3. Copy the URL of the Facebook Page or Profile you want to analyze and paste it into the 'Start URLs' field.
4. Adjust the 'resultsLimit' to control how far back in the timeline the scraper goes.
5. Configure whether you want to scrape comments alongside the posts.
6. Click 'Start'. Download your gathered social data as an Excel or JSON dataset.

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What does the exported data look like?

You can export the results into Excel, CSV, JSON, or HTML. Here is a sample of what the raw JSON data looks like:

{
  "url": "https://www.facebook.com/Apify/posts/123456789",
  "text": "We are thrilled to launch our new AI scraping features today! 🚀",
  "author": "Apify",
  "date": "2026-03-10T14:30:00.000Z",
  "likes": 1500,
  "loves": 300,
  "shares": 120,
  "comments": 450,
  "postComments": [
    {
      "author": "Jane Smith",
      "text": "This is exactly what we needed! Great job team.",
      "date": "2026-03-10T15:00:00.000Z",
      "likes": 15
    }
  ],
  "mediaUrl": "https://scontent-prg1-1.xx.fbcdn.net/v/t39.30808-6/42..."
}