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In this guide, we’ll explain how to scrape LinkedIn data—the most popular career-related social media platform out there.
But scraping data from LinkedIn isn’t as simple as pressing a button—it requires the right tools, strategies, and understanding of both legal and technical aspects.
We’ll scrape LinkedIn information from search, job, company, and public profile pages. All of which is done through straightforward Python code, along with a few parsing tips and tricks. Let’s get started!
LinkedIn scraping refers to the process of extracting publicly available information from LinkedIn profiles or company pages. This data can include job titles, contact details, professional experience, skills, company information, and more. Data scraping allows businesses to automate the process of gathering this valuable data without the need for manual collection.
LinkedIn offers a vast amount of structured data that can be useful for multiple purposes: lead generation, recruitment, market research, competitor analysis, and more. With LinkedIn scraping tools, this task becomes easier and more efficient.
A LinkedIn scraping tool enables valuable data extraction for both businesses and individuals through different use cases.
● Market Research
Market trends and qualifications are fast-changing. Hence, LinkedIn web scraping is beneficial for keeping up with these changes by extracting industry-related data from company or job pages.
● Personalized Job Research
LinkedIn includes thousands of job listing posts across various domains. Scraping data from LinkedIn enables creating alerts for personalized job preferences while also aggregating this data to gain insights into the in-demand skills and job requirements.
● Lead Generation
Scraping leads from LinkedIn provides businesses with a wide range of opportunities by identifying potential leads with common interests. This leads to data that empowers decision-making and helps attract new clients.
Using LinkedIn scraping tools can save you countless hours of manual data entry and research. These tools can help you:
● Extract bulk data: If you’re gathering data for marketing campaigns or lead generation, scraping is much more efficient than manually reviewing LinkedIn profiles.
● Automate data collection: Scraping LinkedIn with an API or scraping tool lets you set it and forget it, running the scraper as often as needed to keep your data fresh.
● Stay competitive: With access to comprehensive professional data, you can outsmart your competitors by tailoring strategies based on real-time insights.
The first step in scraping LinkedIn effectively is choosing the right LinkedIn web scraper. Some solutions are tailored for individual users, while others are enterprise-level, designed to handle large-scale data extraction tasks. Let’s explore the best tools for LinkedIn scraping:
Thordata provides web scraping, screenshot, and extraction APIs for data collection at scale.
● Customizable Scraping: Tailor your scraping needs based on specific data points such as job titles, location, industry, and more.
● Easy Integration: Integrate Thordata’s API into your existing workflows, CRM systems, or marketing automation tools seamlessly.
● Data Accuracy: Thordata’s scraper ensures you get clean, structured, and accurate data with high precision, crucial for lead generation and business analysis.
Scraping LinkedIn data without getting blocked using Thordata is fairly straightforward. All we have to do is replace our HTTP client with the Thordata client, enable the asp parameter, and select a proxy country:
import requests
# Thordata Web Scraper API endpoint and your API key
api_url = “https://api.thordata.com/scrape”
api_key = “Your_Thordata_API_Key”
# Set the URL for the LinkedIn profile you want to scrape
linkedin_url = “https://www.linkedin.com/in/some-profile/”
# Prepare the headers, including your Thordata API key for authentication
headers = {
“Authorization”: f”Bearer {api_key}”,
“Content-Type”: “application/json”
}
# Prepare the data payload
data = {
“url”: linkedin_url,
“render_js”: True, # Enable rendering of JavaScript to scrape dynamic content
“proxy_pool”: “residential_pool”, # Choose proxy pool (residential proxies for high success rate)
“country”: “US”, # Set the proxy location to a specific country (optional)
“asp”: True # Enable anti-scraping protection to bypass LinkedIn blocks (optional)
}
# Make the API request to Thordata
response = requests.post(api_url, headers=headers, json=data)
# Check the response status
if response.status_code == 200:
# Get the scraped content from the response
content = response.json().get(“content”)
# Here you can process the content as per your needs
# Example: print the scraped HTML
print(content)
else:
# Handle errors if the request fails
print(f”Error: {response.status_code}, {response.text}”)
For those looking for simpler, user-friendly solutions, LinkedIn data scrapers are available that provide intuitive interfaces and functionality for extracting data. These tools often come with browser extensions or standalone software that can be easily set up. They allow users to quickly scrape LinkedIn profiles and export data into CSV or Excel formats for further analysis.
|
👨🦱 First Name |
👨🦳 Last Name |
📝 About / Bio |
|---|---|---|
|
👩🏫 Headline / Occupation |
👔 Job Title |
🏢 Current Company Details |
|
🌍 Country |
👥 Number of Followers |
🏢 Industry |
|
🔗 Company LinkedIn URL |
👔 Educational qualifications |
📰 Skills |
|
🌆 Location |
🏢 Certifications |
🏢 Job positions history |
|
ℹ️ Verification info |
ℹ️ Honors |
ℹ️ Languages |
This tutorial covers popular web scraping techniques for education. Interacting with public servers requires diligence and respect, and here’s a good summary of what not to do:
● Do not scrape at rates that could damage the website.
● Do not scrape data that’s not available publicly.
● Do not store PII of EU citizens who are protected by GDPR.
● Do not repurpose the entire public datasets, which can be illegal in some countries.
Scrapfly does not offer legal advice, but these are good general rules to follow in web scraping, and for more, you should consult a lawyer.
When looking for the best LinkedIn scraper, here are some features you should consider:
|
Feature |
Thordata Web Scraper API |
LinkedIn Data Scrapers |
|
Data Accuracy |
High |
Medium |
|
Customization Options |
Extensive |
Limited |
|
Ease of Integration |
Seamless |
Easy-to-use |
|
Data Volume Handling |
Large-scale |
Small-scale |
|
Compliance with LinkedIn |
High |
Medium |
|
Price |
Subscription-based |
Free / Paid |
Before you begin scraping, determine what kind of data you need. Are you looking for LinkedIn profiles, company information, job postings, or something else? Identifying your data needs will help you choose the right scraping tool and avoid unnecessary data extraction.
Throttling your requests is essential to prevent overloading LinkedIn’s servers. This is also a best practice to ensure you don’t get flagged or blocked for scraping.
After scraping LinkedIn data, ensure you clean and validate the data to remove errors, duplicates, and outdated information. Using data cleansing tools will save you time and effort.
When it comes to scraping LinkedIn in 2025, the Thordata web scraper API stands out as a top choice. With its high accuracy, customizable scraping features, and ease of integration into existing workflows, Thordata makes extracting valuable data from LinkedIn simple and efficient. It offers a seamless user experience, especially for businesses and developers looking to automate their data collection processes.
By using Thordata’s scraper, you can focus on gathering quality data without worrying about compliance or managing scraping complexity. Whether you’re in marketing, sales, or recruitment, Thordata’s LinkedIn scraping solution is designed to meet your needs.
Frequently asked questions
Can You Scrape LinkedIn Profiles?
Yes, using LinkedIn scraping tools like Thordata’s web scraper API, you can scrape publicly available information from LinkedIn profiles. However, it’s essential to follow ethical guidelines and LinkedIn’s terms of service to avoid violations.
How Can I Automate LinkedIn Data Scraping?
To automate LinkedIn data scraping, you can use APIs like Thordata’s, which allows you to schedule scraping tasks and automatically collect data at regular intervals, freeing you from manual processes.
Is Scraping LinkedIn Legal?
Scraping LinkedIn can be legally grey, depending on how it’s done. It’s crucial to avoid violating LinkedIn’s terms of service by scraping data responsibly, respecting rate limits, and using official APIs when necessary.
About the author
Jenny is a Content Specialist with a deep passion for digital technology and its impact on business growth. She has an eye for detail and a knack for creatively crafting insightful, results-focused content that educates and inspires. Her expertise lies in helping businesses and individuals navigate the ever-changing digital landscape.
The thordata Blog offers all its content in its original form and solely for informational intent. We do not offer any guarantees regarding the information found on the thordata Blog or any external sites that it may direct you to. It is essential that you seek legal counsel and thoroughly examine the specific terms of service of any website before engaging in any scraping endeavors, or obtain a scraping permit if required.
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