LinkedIn posts data, powered by Bright Data.
This repository provides two approaches to accessing LinkedIn posts data at scale:
- Method 1: Bright Data LinkedIn posts Scraper API (Recommended) - A fully managed, enterprise-grade scraping API that handles proxies, CAPTCHAs, and scaling automatically.
- Method 2: Bright Data LinkedIn posts Datasets - Ready-to-download, pre-collected LinkedIn posts datasets, no scraping required.
- Why Use Bright Data for LinkedIn posts Scraping?
- Method 1: Bright Data LinkedIn posts Scraper API
- Method 2: Bright Data LinkedIn posts Datasets
- Data Collection Approaches
LinkedIn posts scraping comes with several challenges:
- Rate Limiting: LinkedIn posts monitors request frequency and may block IPs that exceed limits.
- CAPTCHA Detection: Automated access may trigger CAPTCHA challenges.
- Authentication Barriers: Some data requires login and the platform detects automated attempts.
- Dynamic Content Loading: JavaScript-rendered content is difficult to scrape with simple HTTP requests.
- IP Blocking: Repeated requests from the same IP may result in blocks.
Bright Data's LinkedIn posts Scraper API solves these problems with:
- ✅ Built-in rotating proxies: Bypass IP-based rate limits automatically
- ✅ CAPTCHA solving: Handles bot detection without any extra setup
- ✅ Structured data output: Receive clean JSON ready for analysis
- ✅ No infrastructure needed: Cloud-managed scraping at any scale
- ✅ 99.9% uptime SLA: Reliable data collection for business-critical workflows
The Bright Data LinkedIn posts Scraper API is a fully managed solution requiring zero infrastructure setup.
- Sign up for a free Bright Data account
- Navigate to the LinkedIn posts Scraper API
- Get your API token from the dashboard
- Install the
requestslibrary:pip install requests - Run any of the scripts in
linkedin-posts_scraper_api_codes/
Collect post data from LinkedIn posts.
| Field | Type | Required | Description |
|---|---|---|---|
url |
string | Yes | The URL of the LinkedIn posts item to scrape |
limit |
integer | No | Maximum number of results to return |
include_errors |
boolean | No | Include error details in the response |
notify |
url | No | Webhook URL to notify when collection is complete |
format |
enum | No | Output format: JSON, NDJSON, JSON Lines, CSV |
{
"author_name": "Jeff Weiner",
"author_title": "Executive Chairman at LinkedIn",
"author_url": "https://www.linkedin.com/in/jeffweiner08/",
"comments_count": 1456,
"hashtags": [
"#futureofwork",
"#AI",
"#leadership"
],
"likes_count": 15234,
"post_id": "ugcPost:7089012345678901",
"posted_at": "2024-06-25T14:00:00Z",
"shares_count": 2103,
"text": "Thrilled to share our latest research on the future of work and AI collaboration. The findings are both inspiring and thought-provoking...",
"url": "https://www.linkedin.com/posts/jeffweiner08_futureofwork-ai-leadership-ugcPost-7089012345678901"
}👉 View Full Python Code
For use cases where you need ready-to-use data without writing any scraping code, the Bright Data LinkedIn posts Dataset offers pre-collected, regularly updated data available for instant download.
Why use the dataset instead of the API?
- 📦 Instant access: No setup, no code, no waiting for collection
- 🔄 Regularly updated: Fresh data refreshed on a consistent schedule
- 📊 Multiple formats: Download as JSON, JSONL, or CSV
- 🌍 Massive scale: Millions of records across all major LinkedIn posts categories
- ✅ Fully compliant: Ethically sourced and legally cleared data
👉 Explore the LinkedIn posts Dataset
| Feature | Bright Data Scraper API | Bright Data Datasets |
|---|---|---|
| Setup required | API token only | None |
| Real-time data | ✅ Yes | ❌ Pre-collected |
| Custom queries | ✅ Full control | ❌ Fixed schema |
| Proxies included | ✅ Built-in rotating | N/A |
| CAPTCHA solving | ✅ Automatic | N/A |
| Scale | Unlimited | Unlimited |
| Structured output | ✅ JSON / NDJSON / JSON Lines / CSV | ✅ JSON / JSONL / CSV |
| Support | Enterprise 24/7 | Enterprise 24/7 |
🔗 Learn more: https://brightdata.com/products/web-scraper/linkedin