Pricing

$19.99/month + usage

Facebook Reviews Scraper

⭐ Facebook Reviews Scraper extracts Facebook Page reviews at scale — ratings, comments, dates, reviewer names, reactions & owner replies. 🔎 Export CSV/JSON, schedule runs, and analyze sentiment. 🚀 Ideal for reputation management, CX insights & social proof.

Pricing

$19.99/month + usage

Rating

0.0

(0)

Developer

ScrapeEngine

Actor stats

Bookmarked

Total users

Monthly active users

3 days ago

Last modified

Categories

Lead generation

Social media

Automation

You can access the Facebook Reviews Scraper programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.

Python

JavaScript

CLI

OpenAPI

HTTP

MCP

1from apify_client import ApifyClient
2
3# Initialize the ApifyClient with your Apify API token
4# Replace '<YOUR_API_TOKEN>' with your token.
5client = ApifyClient("<YOUR_API_TOKEN>")
6
7# Prepare the Actor input
8run_input = { "inputs": ["https://www.facebook.com/mrbeast"] }
9
10# Run the Actor and wait for it to finish
11run = client.actor("scrapeengine/facebook-reviews-scraper").call(run_input=run_input)
12
13# Fetch and print Actor results from the run's dataset (if there are any)
14print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
15for item in client.dataset(run["defaultDatasetId"]).iterate_items():
16    print(item)
17
18# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

Facebook Reviews Scraper API in Python

The Apify API client for Python is the official library that allows you to use Facebook Reviews Scraper API in Python, providing convenience functions and automatic retries on errors.

Install the apify-client

$pip install apify-client

Other API clients include:

Facebook Reviews Scraper API in JavaScript

Facebook Reviews Scraper API through CLI

Facebook Reviews Scraper OpenAPI definition

Facebook Reviews Scraper API

Facebook Reviews Scraper

scrapium/facebook-reviews-scraper

Scrapium

Facebook Reviews Scraper

scrapemesh/facebook-reviews-scraper

ScrapeMesh

Facebook Reviews Scraper

scraply/facebook-reviews-scraper

Scraply

Facebook Reviews Scraper

scrapebase/facebook-reviews-scraper

ScrapeBase

Facebook Reviews Scraper

scraperforge/facebook-reviews-scraper

ScraperForge

Facebook Reviews Scraper

simpleapi/facebook-reviews-scraper

Facebook Reviews Scraper extracts reviews from Facebook Pages, capturing reviewer names, ratings, comments, timestamps, and helpfulness details. Ideal for sentiment analysis, brand monitoring, customer research, and automating structured Facebook review data collection at scale.

SimpleAPI

Facebook Reviews Scraper

scrapier/facebook-reviews-scraper

Scrape Facebook page reviews with the Facebook Reviews Scraper. Extract reviewer names, ratings, comments, timestamps, and helpfulness reactions. Ideal for sentiment analysis, market research, and brand monitoring. Fast, accurate, and scalable for single or multiple pages.

Scrapier

Facebook Reviews Scraper

api-empire/facebook-reviews-scraper

Facebook Reviews Scraper extracts reviews from any public Facebook page. Capture reviewer names, ratings, comments, timestamps, and sentiment details. Ideal for brand monitoring, customer analysis, market research, and workflows that need clean structured review data.

API Empire

Facebook Comments Scraper

scraper-engine/facebook-comments-scraper

💬 Facebook Comments Scraper extracts post comments at scale—text, authors, timestamps, reactions, and threaded replies. ⚙️ Export CSV/JSON for analytics, sentiment, and reporting. 🚀 Ideal for social listening, CX, and research. ✅ Use on public or authorized data.

Scraper Engine

Scrape Facebook Page Reviews by Page ID - Cookieless

patient_discovery/facebook-page-reviews

Extract Facebook page reviews without login or cookies. Get ratings, recommendation status, review text, reactions, photos, and reviewer profiles in JSON or CSV. Ideal for sentiment analysis, reputation monitoring, competitive intelligence, and customer feedback research at scale.