Facebook Reviews Scraper

Facebook Reviews Scraper

The Facebook Reviews Scraper is a production-ready Facebook reviews scraping tool that extracts structured recommendations, ratings signals, comments counts, timestamps, and reviewer details from public Facebook Pages. Built for marketers, developers, data analysts, and researchers, this Facebook page reviews scraper helps you scrape Facebook reviews at scale, export Facebook reviews to CSV/JSON, and automate pipelines for sentiment analysis and reputation monitoring. Use it as a Facebook reviews extractor for competitive tracking or as a Python Facebook reviews scraper in your data workflows — all without manual copy-paste.

What data / output can you get?

Below are the exact fields the actor outputs for each review. You can export Facebook reviews to CSV, JSON, or Excel directly from the Apify dataset, and also get an aggregated JSON by page in the Key-Value Store.

Data field	Description	Example value
facebookUrl	The Facebook page URL where the review/recommendation appears	https://www.facebook.com/mrbeast
id	Unique review identifier (often Base64-like)	UzpfSTYxNTg0MzE3MjA0OTY4OjEyMjEwOTkzMzE4OTE0MzkwNjoxMjIxMDk5MzMxODkxNDM5MDY=
user.id	Reviewer’s Facebook ID	pfbid022DhB36PVT9anEH47J7WQu78JYMNhaEGeHHKAhyPXJVNjusrH3TCi...
user.name	Reviewer’s display name	Helen Head
user.profileUrl	Link to the reviewer’s profile	https://www.facebook.com/people/Helen-Head/pfbid022DhB...
user.profilePic	Reviewer’s profile picture URL (may be null)	null
date	Review creation date in ISO 8601 (UTC)	2025-12-23T18:12:27.000Z
url	Direct link to the review post	https://www.facebook.com/permalink.php?story_fbid=...
isRecommended	Whether the reviewer recommended the page (true/false)	true
text	Full text content of the review/recommendation	I’m at the homeless shelter...
likesCount	Number of reactions/likes	1
commentsCount	Number of comments on the review	0
facebookId	Facebook feedback ID	ZmVlZGJhY2s6MTIyMTA5OTMzMTg5MTQzOTA2
postFacebookId	Facebook post ID	122109933189143906
pageName	Name of the Facebook Page being reviewed	MrBeast

Notes:

• Results are available as individual items in the Dataset and as aggregated JSON grouped by page name (Key-Value Store key: OUTPUT).
• You can export Facebook reviews to CSV, JSON, or Excel from the Dataset. For teams, it’s easy to push Facebook reviews to Google Sheets using Apify integrations.

Key features

• 🚀 Asynchronous, concurrent scraping
  Built with aiohttp and tuned concurrency (3 pages in parallel) for automated Facebook reviews extraction at scale.

• 🔄 Cursor-based GraphQL pagination
  Uses Facebook’s GraphQL cursor flow to fetch complete review/recommendation feeds reliably.

• 🧹 Smart deduplication
  Deduplicates by unique review IDs to ensure clean, analysis-ready datasets.

• 🧭 URL normalization for pages & usernames
  Accepts page URLs or simple usernames/keywords and normalizes them into proper /reviews endpoints automatically.

• ↕️ Flexible sorting (by output order)
  Sorting supported in code for newest, oldest, or most_relevant (by likes + comments), enabling a focused Facebook recommendations scraper and Facebook ratings scraper workflow.

• 🧪 Resilient proxy fallback
  Automatic staged fallback: no proxy/input proxy → DATACENTER proxy → RESIDENTIAL proxy (with retries) to reduce blocks and keep runs stable.

• 📦 Instant output streaming + aggregation
  Each review is pushed to the Dataset as soon as it’s parsed, and aggregated output (by pageName) is saved to the Key-Value Store (key: OUTPUT).

• 💾 Easy exports & integrations
  Download Facebook reviews as CSV/JSON/Excel and plug into your analytics or send Facebook reviews to Google Sheets using Apify’s platform features.

• 🐍 Developer friendly (Python)
  Built as a Python Facebook reviews scraper on Apify — integrate via API, schedule jobs, and connect to your data pipelines.

How to use Facebook Reviews Scraper - step by step

1. Create or log in to your Apify account
   Visit https://console.apify.com and sign in or create a free account.

2. Open the actor
   Search for “Facebook Reviews Scraper” in the Apify Console and open the actor page.

3. Add input data
   In the Input tab, paste Facebook page URLs or usernames into the inputs array (e.g., https://www.facebook.com/mrbeast or mrbeast).

4. Configure limits and proxies
   Optionally set maxItems (per page) and choose proxyConfiguration. By default, useApifyProxy is false; the actor will auto-fallback to datacenter and then residential proxies if needed.

5. Start the run
   Click Start. The actor normalizes inputs to /reviews, resolves dynamic IDs, and begins cursor-based pagination.

6. Monitor progress
   Watch logs for pagination status, retries, and proxy stages. Reviews are pushed to the Dataset immediately as they’re parsed.

7. Download results

   • Dataset: View individual review records and export as CSV, JSON, or Excel.
   • Key-Value Store: Open the OUTPUT key to download aggregated JSON grouped by pageName.

Pro tip: Use the Apify API to trigger runs programmatically and pipe Facebook reviews to Google Sheets or your warehouse for analytics.

Use cases

Use case	Description
Reputation management for brands	Track recommendations and feedback to improve response times and customer satisfaction.
Competitive benchmarking	Monitor competitor pages to analyze sentiment and engagement trends over time.
Market research & analytics	Aggregate reviews across multiple business pages for category-level insights.
Voice-of-customer programs	Export Facebook reviews to CSV/JSON and feed NLP pipelines for sentiment and topic modeling.
Local SEO & ratings tracking	Use this Facebook business page reviews scraper to monitor public reputation signals.
Support & moderation workflows	Identify high-engagement reviews (likes/comments) for prioritized responses.
Data pipelines & BI	Automate runs and integrate outputs via API for dashboards and reporting.
Academic & social research	Collect structured public recommendations for longitudinal studies and content analysis.

Why choose Facebook Reviews Scraper?

The Facebook Reviews Scraper is built for precision, scale, and reliability — a production-ready Facebook reviews scraping tool you can trust.

• ✅ Accurate, structured outputs: Consistent field names and clean review objects for analytics downstream.
• 🌍 Public data only: Works on publicly available Facebook Pages without authentication.
• ⚙️ Batch-ready scale: Scrape multiple pages concurrently with robust pagination and deduplication.
• 🧪 Resilient anti-blocking: Automatic proxy fallback across input, datacenter, and residential stages with retries.
• 🐍 Developer-first: Python-based, easy to automate via the Apify API for continuous data delivery.
• 💾 Flexible exports: Download Facebook reviews or export to CSV/JSON/Excel — integrate with BI or Google Sheets through Apify.
• 🛡️ More reliable than extensions: No flaky browser add-ons; infrastructure-grade actor with logging and retry logic.

In short, it’s a fast, stable Facebook page recommendations extractor built for real-world data workflows.

Is it legal / ethical to use Facebook Reviews Scraper?

Yes — when used responsibly. This actor collects data from publicly available Facebook Pages only and does not access private or authenticated content.

Guidelines for compliant use:

• Scrape public Pages and respect platform terms of service.
• Ensure your usage complies with applicable privacy and data protection laws (e.g., GDPR, CCPA).
• Avoid collecting or using sensitive personal data; use aggregated insights where possible.
• Consult your legal team for edge cases and jurisdiction-specific requirements.

Input parameters & output format

Example JSON input (basic)

{
  "inputs": [
    "https://www.facebook.com/mrbeast",
    "tesla",
    "nike"
  ],
  "maxItems": 100,
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}

Input fields (from schema):

• inputs (array, required): List of Facebook page URLs (e.g., https://www.facebook.com/mrbeast) or usernames (e.g., mrbeast). Keywords require resolvable page context. Default: none.
• maxItems (integer, optional): Maximum number of reviews to scrape per page. The actor stops pagination once this limit is reached. Default: 100. Min: 1, Max: 10000.
• proxyConfiguration (object, optional): Choose which proxies to use. By default, no proxy is used. If Facebook rejects or blocks the request, the actor automatically falls back to datacenter, then residential proxies with retries. Default: {"useApifyProxy": false}.

Advanced options recognized by the actor (from source code):

• sortOrder or sort_order (string, optional): Sorting mode for the final output. Supported values: newest (default), oldest, most_relevant.

Dataset output (one item per review)

{
  "facebookUrl": "https://www.facebook.com/mrbeast",
  "id": "UzpfSTYxNTg0MzE3MjA0OTY4OjEyMjEwOTkzMzE4OTE0MzkwNjoxMjIxMDk5MzMxODkxNDM5MDY=",
  "user": {
    "id": "pfbid022DhB36PVT9anEH47J7WQu78JYMNhaEGeHHKAhyPXJVNjusrH3TCierbYBcaA7NTBl",
    "name": "Helen Head",
    "profileUrl": "https://www.facebook.com/people/Helen-Head/pfbid022DhB36PVT9anEH47J7WQu78JYMNhaEGeHHKAhyPXJVNjusrH3TCierbYBcaA7NTBl/",
    "profilePic": null
  },
  "date": "2025-12-23T18:12:27.000Z",
  "url": "https://www.facebook.com/permalink.php?story_fbid=pfbid036zKdeTsZRHzcZspm8CNjzv3jSuSQFmbjNc6h4FPwLvsBmjYU3ibcHqX4HSukzQakl&id=61584317204968",
  "isRecommended": true,
  "text": "I'm at the homeless shelter ...",
  "likesCount": 1,
  "commentsCount": 0,
  "facebookId": "ZmVlZGJhY2s6MTIyMTA5OTMzMTg5MTQzOTA2",
  "postFacebookId": "122109933189143906",
  "pageName": "MrBeast"
}

Aggregated Key-Value Store output (key: OUTPUT)

{
  "MrBeast": [
    {
      "facebookUrl": "https://www.facebook.com/mrbeast",
      "id": "UzpfSTYxNTg0MzE3MjA0OTY4OjEyMjEwOTkzMzE4OTE0MzkwNjoxMjIxMDk5MzMxODkxNDM5MDY=",
      "user": {
        "id": "pfbid022DhB36PVT9anEH47J7WQu78JYMNhaEGeHHKAhyPXJVNjusrH3TCierbYBcaA7NTBl",
        "name": "Helen Head",
        "profileUrl": "https://www.facebook.com/people/Helen-Head/pfbid022DhB36PVT9anEH47J7WQu78JYMNhaEGeHHKAhyPXJVNjusrH3TCierbYBcaA7NTBl/",
        "profilePic": null
      },
      "date": "2025-12-23T18:12:27.000Z",
      "url": "https://www.facebook.com/permalink.php?story_fbid=pfbid036zKdeTsZRHzcZspm8CNjzv3jSuSQFmbjNc6h4FPwLvsBmjYU3ibcHqX4HSukzQakl&id=61584317204968",
      "isRecommended": true,
      "text": "I'm at the homeless shelter ...",
      "likesCount": 1,
      "commentsCount": 0,
      "facebookId": "ZmVlZGJhY2s6MTIyMTA5OTMzMTg5MTQzOTA2",
      "postFacebookId": "122109933189143906",
      "pageName": "MrBeast"
    }
  ]
}

Field notes:

• pageName may be missing for certain stories; aggregated keys fall back to a derived page name or “Unknown”.
• user.profilePic may be null if unavailable.

FAQ

Do I need a Facebook login or cookies?

No. The actor scrapes publicly available Facebook Page reviews and recommendations without authentication.

How many pages can I process at once?

The scraper processes multiple pages concurrently (up to 3 in parallel) for efficient batch runs. Add multiple URLs or usernames to the inputs array to scrape multiple pages in one run.

How many reviews does it collect per page?

You control this via maxItems (default 100). The actor paginates using GraphQL cursors and stops when your limit is reached or when there are no more items.

Can I sort the results?

Yes. The actor recognizes sortOrder (or sort_order) with newest, oldest, or most_relevant to sort the final output.

What happens if Facebook blocks my requests?

The actor includes a staged proxy fallback: it will try your input/no proxy first, then automatically switch to DATACENTER proxy, and finally to RESIDENTIAL proxy with retries if needed.

What formats can I download?

You can download the Dataset as JSON, CSV, or Excel. The Key-Value Store also contains aggregated JSON (key: OUTPUT) grouped by page name.

Does it extract Facebook recommendations and ratings signals?

Yes. It captures isRecommended along with engagement metrics (likesCount, commentsCount), making it suitable as a Facebook recommendations scraper and Facebook ratings scraper.

Is there an API or Python integration?

Yes. This is a Python Facebook reviews scraper running on Apify. You can trigger runs and fetch datasets via the Apify API for automation.

Closing CTA / Final thoughts

The Facebook Reviews Scraper is built for fast, reliable extraction of public Facebook Page reviews and recommendations. With concurrent scraping, robust pagination, proxy fallback, and clean JSON outputs, it’s ideal for marketers, developers, analysts, and researchers who need to download Facebook reviews, export Facebook reviews to CSV/JSON, and automate insights at scale. Use it as your Facebook reviews API endpoint in workflows or as a Facebook reviews to Google Sheets pipeline via Apify integrations. Start extracting smarter, richer customer feedback today.