How to Scrape Facebook: 6 Proven Techniques for Extracting Data and Profiles

Justin Shin
Are you looking for ways to collect publicly available data from the Facebook platform? then you are on the right page as the article below provides you the different methods you can achieve that.

In the modern digital era, social media platforms have taken over our daily lives. They have more excellent sources of pertinent data than ever before for a variety of use cases. Facebook is one of these platforms that is most widely used. Facebook is not only a social network; with more than 2.9 billion monthly active members globally, it is also a huge database chock full of user-generated content. A significant chunk of this data can be used to design goods more quickly and comprehend clients better.

Facebook has become a vital tool for companies looking to connect with and engage with their target market. However, manually gathering Facebook data might take a lot of time and resources. Particularly when it comes to large-scale data collection methods, manual web scraping is prone to mistakes and inaccuracies.

Facebook provides an API for gathering user profiles and platform information, but it has its own constraints and limitations. As such, I'll be sharing with you a few techniques for getting unrestricted access to the quantity and quality of data you need from Facebook.

However, before we move forward, I would like to give you some background on what Facebook scraping really is.

Table Of Contents

What is Facebook Scraping?

Facebook scraping is the process of collecting information from Facebook's website that is openly accessible. Data such as user profiles, posts, comments, photos, and other platform information may be included in the data that is extracted. Although it is possible to scrape Facebook manually, the term "Facebook scraping" typically refers to automated procedures carried out with a web scraper.

After gathering the data, it is processed and exported into formats like CSV and JSON for easy analysis. Scraping Facebook is a challenging task, though. This is due to Facebook's highly efficient anti-bot technology. Nevertheless, as I already mentioned, I'll be sharing some of the best methods for scraping Facebook without encountering issues with the anti-bot system with you.

Web scraping Tips to follow

  • Web scraping can be useful for gathering public data from websites, but it should be done ethically and legally. Make sure you understand and follow a website's terms of service.
  • Consider using a website's APIs if available, as they are designed for programmatic access. Scraping may be detected and blocked.
  • Be mindful of only collecting data that is needed for your specific purpose. Avoid harvesting excessive personal information without users' consent.
  • Use scrapers judiciously and do not create unnecessary load on websites you are scraping. Consider rate limits and caching data when possible.
  • Web scraping is technically challenging to do well at scale. Expect to handle issues like CAPTCHAs, blocked IPs, and changes to page structures.
  • Consider consulting with legal counsel to understand risks before building or deploying a web scraper, especially for commercial purposes.

Methods of Scraping Facebook

Discussed below are some of the popular methods of scraping Facebook you can use.

1. Scraping Facebook with Python

Building a custom scraping solution with Python is a very effective approach to extracting relevant information from Facebook. Given that Python is among the strongest programming languages for this, this is arguably one of the best strategies. Many open-source modules and frameworks for web scraping are available in Python, including Beautiful Soup, Selenium, and Scrapy.

To get started, you will need to install Python on your machine. You should note that for the scraper to work, you’ll need to use a proxy server and a headless browser library.

I'll be using Facebook-page-scraper 3.0.1, a Python-based scraper, for this approach. It doesn't place a cap on the number of requests you can make and comes with the majority of the web scraping functionality already implemented.

As such, you need to get the Python JSON library before installing Facebook-page-scraper. They are available at this GitHub link. You can install this package by entering the pip install command into your CMD after completing the necessary installation:

pip install facebook-page-scraper

Modifying the Scraper

Facebook just made a few modifications that have an effect on the scraper we'll be using. As such, modifications have also been made to the scraper files to help you scrape several pages or bypass the cookie consent window. This is an adjustment to both the and files.

Scraping Facebook Posts

  1. In a directory of your choice, make a new text file and rename it Open the document and begin writing the main code afterwards.
  2. Import scraper using the code below:

from facebook_page_scraper import Facebook_scraper So, without waiting much time, this is the full script below: from facebook_page_scraper import Facebook_scraper

page_list = ['jimmyfoxx','FoxNews','NEWMAX','lebronjames'] proxy_port = 10001 posts_count = 150 browser = "chrome" timeout = 600 headless = False

#Proxy for this data scraping

proxy = f'{proxy_port}'

#This is to initialize the scraper

scraper = Facebook_scraper(page, posts_count, browser, proxy=proxy, timeout=timeout, headless=headless)

# Scraping and printing out the result into the console window:

json_data = scraper.scrap_to_json() print(json_data)

# Scraping and writing into output CSV file: # Directory for output if you want to scrape directly to CSV

directory = "C:\\facebook_scraping_results"    filename = page scraper.scrap_to_csv(filename, directory) proxy_port += 1

So, after importing the scraper, I selected a number of public profiles and put them as string values in the code above. The headless browser and proxies had to be configured after that. In this case, I would advise choosing mobile or static residential proxies. I then typed 150 posts as the number of posts I wanted to scrape for the post count variable. Additionally, I had to mention the browser. You have a choice between using Firefox or Google Chrome.

The timeout variable needed to be set as well. That means scraping will stop after a predetermined amount of inactivity. The time should be expressed in seconds. As such, 600 seconds is the norm, though you can change it to suit your needs. Let's move on to the variable for headless browsers. I entered the boolean false to observe the scraper in operation. Otherwise, writing true will run the code in the background. I then went ahead and initialized the scraper.

There are two ways the results can be presented. The first step is to print the outcome in the terminal window. If not, you can export it as a CSV file. To achieve this, I had to make a folder called facebook_scraping_results—or any other name that would work—and then leave it as a directory variable. You can choose whichever output presentation you feel most comfortable with.

Last but not least, I included code for proxy rotation, which will change your IP after each connection. This basically keeps you out of IP bans and in a safe spot. The code can now be saved and executed in CMD.



2. Using Facebook Scrapers

Using customized scrapers is another way of extracting Facebook data. They are third-party service providers' scrapers. These scrapers are available to assist in overcoming the challenges and restrictions associated with using Facebook's provided API.

One of these is the Facebook Page Scraper by Apify. This is a straightforward and effective tool that enables you to extract essential information from Facebook pages. You only need to enter the page URL and select "Save & Start" to get this data. As such, you can extract Facebook page names, the page URL, categories, likes, and other publicly available data with this tool. Interestingly, Apify’s Facebook Page Scraper remains one of the best tools for developers.

This is a result of its excellent application integration compatibility. Here's how to use this tool to scrape Facebook data:

1. To begin, you must use your email to register for a free Apify account. After that, you launch the Facebook Pages Scraper.

2. Add a single or a few Facebook page URLs if you want to scrape their information. Click 'Save & Start' after inputting the Facebook URLs you want to use, then wait for the data to be extracted.

3. The scraped data is available for download in JSON, CSV, Excel, XML, RSS or HTML table.

Phantom Buster, Facedominator, and Octaparse are a few other trustworthy Facebook scrapers. These ones are considerably more specialized for Facebook scraping. Phantom Buster, for instance, works well for collecting user-generated information from Facebook groups and communities. Octaparse is a great substitute for Apify's Facebook Page Scraper,making it the best choice for those without programming skills.



Using Web Scraper API

As was previously noted, Facebook provides an API for scraping their publicly accessible data; however, it has a drawback. Fortunately, you can overcome this by using trustworthy third-party web scraper API that are available on the market.

One of the best you can find on the market is ScraperAPI. For you to scrape any Facebook page with a straightforward API call, this program has gone through the challenging process of configuring headless browsers, locating proxies, and handling CAPTCHAs. Even further customization of the API scraper is possible with some code-based web scraping solutions, depending on your individual needs.

It is simple to use ScraperAPI. The API will provide the HTML response from the URL you want to scrape if you simply feed it the URL you want to scrape and your API key. There are five ways to use this provider's APIs to do this. But for the time being, we'll simply be considering the "API Endpoint Method."

  1. You have to first understand that requests are authenticated using API keys provided by ScraperAPI. You must register for an account and include your own API key in each request in order to access the API.
  2. For you to send GET requests, ScraperAPI exposes a single API endpoint. The HTML response for that URL will be returned by the API by simply sending a GET request to containing the two query string parameters.
  3. Your requests should be formatted as follows when sent to the API endpoint:

"" Below is the sample code import requests

payload = {'api_key': 'APIKEY', 'url': ''} r = requests.get('', params=payload) print(r.text) # Scrapy users can simply replace the urls in their start_urls and parse function # ...other scrapy setup code start_urls = ['' + url] def parse(self, response): # ...your parsing logic here yield scrapy.Request('' + url, self.parse)
  1. When submitting a request to the API endpoint, simply add the necessary query parameters to the end of the ScraperAPI URL to enable additional API functionality. For instance, add render=true to the request if you want Javascript rendering to be enabled.

Do well to visit ScraperAPI documentation to learn more.



3. Using General Purpose Data Extraction Tools

When we talk about general-purpose data extraction technologies, we essentially mean the majority of proxy providers' third-party web scraping services. These scrapers include proxy options that ensure the security of your identity. Bright Data is one well-known proxy provider that provides this. For scraping Facebook data at scale, Bright Data provides a scraping browser solution. Additionally, they provide compatibility for Puppeteer, Playwright, and Selenium for these data extraction technologies. It could be argued that this is more potent than automatic and headless browsers. They come with in-built unblocking and proxy technology.

To use the Scraping Browser solution on Bright Data to scrape Facebook, follow these steps:

  1. Register with the platform. At the moment, Bright Data provides a free trial that can be easily and quickly registered for. When adding your payment method, keep in mind that you will receive a $5 credit to get you started. You need to log into your Bright Data control panel after that.
  2. Go to the 'My Proxies' page and select 'Scraping Browser,' then click 'Get Started' to build your new Scraping Browser proxy. If you already have a proxy running, just select 'Add proxy' on the top right.
  3. Choose and enter a name for the new Scraping Browser proxy zone on the 'Create a new proxy' page. Since the zone's name cannot be modified once it has been formed, please choose a meaningful name. You can now build your first Scraping Browser session in Node.js or Python after confirming your account. Your API credentials are located on the 'Access Parameters' page of your proxy zone. Your Username (Customer_ID), the name of the Zone, and the Password would be included in this. They will be used during the integration. Install Puppeteer-core first if you plan to use Node.js.

npm i puppeteer-core

The script would look like this:

const puppeteer = require('puppeteer-core'); // should look like 'brd-customer--zone-:' const auth='USERNAME:PASSWORD'; async function run(){   let browser;   try {     browser = await puppeteer.connect({browserWSEndpoint: `wss://${auth}`});     const page = await browser.newPage();     page.setDefaultNavigationTimeout(2*60*1000);     await page.goto('');     const html = await page.evaluate(() => document.documentElement.outerHTML);     console.log(html);   }   catch(e) {     console.error('run failed', e);   }   finally {     await browser?.close();   } } if (require.main==module)      run(); After this, you can run the script, node script.js

Developers can use code templates and pre-built JavaScript functions in Bright Data's web scraper IDE. This can drastically cut down on both the development and Facebook scraping durations.



4. Scraping Facebook with RPA

Facebook scraping with Robotic Process Automation (RPA) can minimize the workload on a scraper by automating data collection operations. UiPath Studio is, however, one of the best RPA tools for scraping Facebook.

To scrape Facebook with UiPath Studio, you need to:

1. Create a directory where UiPath Studio will be scraping the data.

2. To scrape the data, you need to navigate to UiPath Studio to trigger the process.

3. To trigger the process, click the ‘Debug File’ dropdown menu.

4. Next, scroll down and click ‘Run’.

5. The bot will automatically create a folder with the run date after it has been triggered.

6. Next, login to Facebook and navigate to the target group page or pages.

7. Following that, the bot will scrape all post data from the previous 24 hours.

Once everything is done, the group's data will be copied into a spreadsheet located inside the folder with the run date. This procedure will be repeated for each group.



5. HTML Parsing using JavaScript

Since Facebook is built largely on JavaScript, you can scrape its data by parsing the HTML using JavaScript. As a result, JavaScript and Node.js both provide a variety of modules that facilitate Facebook scraping. It is possible to render Facebook feeds based on topic channels using Facebook oEmbed endpoints, using Node.js puppeteer as the automation tool and MongoDB to store the collected feed data.

For the most part, Facebook's oEmbed endpoints let you embed HTML and simple information for pages, posts, and videos in order to show them on another website or app.

To do this;

1. As the first step, we need to add the initPuppeteer() method, which imports the puppeteer library.

2. This would start the browser, create a new page, set the browser width and height, and override permissions.

3. Next, you need to add some common configuration messages to a separate file like this.

4. After that, you should add a loginFacebook() function that visits the Facebook website, waits until the network is idle, and then performs the login action as shown below. Note, if the actions are too fast, our bot will be easily detected by Facebook. To tackle this, you can set a random timeout to wait for action.

5. Next, you can now start the scraping based on filter tags such as @mentions/keywords/hashtags. Hence, your next step would be to direct it to the Facebook page based on the filter tag as below.

const page_url = config.base_url + filter_tag;await, {waitUntil: "networkidle2",});

To check the availability of the page to start the scraping steps, follow the code here.

6. Next, if the Facebook page is available for the relevant filter tag, you can go ahead and scroll over the page and render the feeds to the DOM content with this code. Here, you can configure the number of posts to be scraped using post_count.

7. Moving on, identify the posts to be extracted because, in the previous step, we finished the scrolling logic based on the div[role=article] tag; however, it includes some other text contents too. So, we need to filter those out. Hence, you can identify that if it’s a post to be extracted, its ariaLabel is a null value. Based on that, we’re going to add a filter as it is here. For each post, we are going to return text content and inner HTML.

8. Next, you can loop over the filter list and extract the post content, share count, reaction count, comment count, ane timestamp of the post.

9. To extract these figures, we need to first parse the post-inner HTML through an HTML parser and get the root HTML. For that, we can use the node-html-parser. This will generate a simplified DOM tree with element query support.

import { parse } from "node-html-parser"; const root_html = parse(filtered_list[i].html);

10. Also, we can format the data counts represented here.

11. Most importantly, to extract the post URL to render the Facebook feeds in the web app using Facebook oEmbed, follow the code here. From the post actions, we can go ahead and extract the feed from oEmbed. Using this string, we can extract the post URL and post ID, which is done here.

12. Lastly, we should update the MongoDB with the extracted Facebook feed record in the following format:

let dataObj = { post_id: post_id, post_text: post_text, screen_name: filter_tag, post_created_at: ymd_timestamp, attributes: { share_count: share_count, comment_count: comment_count, reaction_count: reaction_count, page_link: page_url, link: post_url, }, time_stamp: Math.round(new Date().getTime() / 1000), };

13. Follow this code for the final step.

However, you should know that there are limitations to this technique.




Q. What Facebook Data Can You Scrape?

You can use these methods to access posts, likes, comments, profiles, contact information, and reviews, among other Facebook data. In essence, these are publicly available data. Additional guidelines, such as the obligation to warn the person and provide them the option to opt out, apply if you want to gather personal information, which is extremely likely to happen. Always seek legal advice to ensure you're taking the appropriate course of action.

Q. What Are the Possible Use Cases of Data Scraped from Facebook?

Based on the robust nature of the Facebook platform, the data extracted can play a vital role. For businesses, these data are good for competitive analysis, sentimental analysis, market research, and a whole lot of other uses.

Scraping publicly accessible data is acceptable as long as you follow Facebook's terms of service. Facebook has severe restrictions against web scraping, and it is considered illegal and unlawful to scrape data from the platform without permission.


So far, we have discussed some of the top ways to scrape Facebook. Facebook scraping can gather data for marketing research, sentiment analysis, competitive analysis, and a few other use cases. Depending on what the use case may be or your knowledge of programming, this article should help guide your Facebook scraping choices. These Facebook data extraction techniques have been carefully chosen after thorough evaluation, so I sincerely hope you will find them useful.

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