# Linkedin Post Reposts/Reshares Scraper (No Cookie) (`datadoping/linkedin-post-repost-scraper`) Actor

For just $1.2 per 1,000 reposts, scrape LinkedIn reposts/reshares of a post and extract full content, engagement stats, and reposter details using post URL. Note: If you're on free tier you can only scrape 4 posts and 100 reposts per profile per run (12 posts in total)

- **URL**: https://apify.com/datadoping/linkedin-post-repost-scraper.md
- **Developed by:** [Data Doping](https://apify.com/datadoping) (community)
- **Categories:** Automation, Social media, Lead generation
- **Stats:** 109 total users, 13 monthly users, 100.0% runs succeeded, 3 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.20 / 1,000 reposts

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

🔍 What is LinkedIn Post Reposts Scraper?

LinkedIn Post Reposts Scraper automates the process of gathering publicly available reposts from LinkedIn posts. Simply provide one or more LinkedIn post URLs, and the scraper will fetch comprehensive repost details such as:

**Repost Content:**

- Repost URLs and timestamps
- Reposter information (name, profile picture, profile URL)
- Original post details and statistics

**Engagement Data:**

- Total reaction counts
- Individual reaction types (like, appreciation, empathy, interest, praise)
- Comment counts and share statistics
- Repost timestamps (both absolute and relative)

All extracted data is limited strictly to public information—nothing private or sensitive is collected.

💡 Why Scrape LinkedIn Post Reposts?

LinkedIn reposts provide valuable insights for professionals and businesses:

🔎 **Content Amplification Analysis**: Analyze which posts get the most reposts and understand content virality patterns.

🧠 **Network Insights**: Understand how content spreads through professional networks and identify influential reposters.

📈 **Social Listening**: Monitor how your content or industry topics are being shared across LinkedIn.

🤝 **Relationship Building**: Identify active content amplifiers and potential networking opportunities.

📊 **Content Strategy**: Research what content generates meaningful reposts and engagement.

🎯 **Brand Monitoring**: Track how your brand content is being shared and amplified.

⚖️ Is it Legal to Scrape LinkedIn Reposts?

We prioritize ethical scraping practices.

This scraper only extracts information that users have chosen to display publicly on their LinkedIn posts. It does not access private data, restricted content, or information behind login walls. All data collection follows LinkedIn's robots.txt guidelines and respects rate limits.

🚀 How to Use

1. **Input Format**: Provide LinkedIn post URLs
   - URL: `hhttps://www.linkedin.com/posts/linkedin_add-job-preferences-activity-7208418413906464769-P2hn`

2. **Reposts Limit**: Set maximum number of reposts to scrape per post (minimum 10, default 100)

3. **Error Handling**: Invalid post URLs or malformed URLs will be logged as errors in the dataset

4. **Freemium Limits**: Free users are limited to 4 posts per run with maximum 100 reposts per post (12 posts in total)

📊 Output Data Structure

The scraper returns comprehensive repost data including:

- **Repost Content**: URLs, timestamps, and metadata
- **Reposter Info**: Name, profile picture, and profile URL
- **Engagement**: Reaction counts and interaction data

🔧 Technical Features

- **Error Handling**: Comprehensive error reporting for failed requests
- **Resume Capability**: Can resume interrupted scraping sessions
- **Concurrent Processing**: Multiple workers for efficient data collection

⚠️ Important Notes

- Only LinkedIn posts are supported (other URLs will return errors)
- All data is publicly available information only
- Free tier limited to 4 posts per run with maximum 100 reposts per post (12 posts in total)
- Premium users have no limits
- Minimum 10 reposts per post (configurable maximum)

### Input Schema

```json
{
  "post_urls": [
    "https://www.linkedin.com/posts/linkedin_add-job-preferences-activity-7208418413906464769-P2hn",
    "https://www.linkedin.com/posts/0987654321"
  ],
  "max_reposts": 100
}
```

# Actor input Schema

## `post_urls` (type: `array`):

List of LinkedIn post URLs to scrape reposts from. Enter one URL per line.

## `max_reposts` (type: `integer`):

Maximum number of reposts to scrape from each post. Minimum is 10 reposts. Default is 100.

## Actor input object example

```json
{
  "post_urls": [
    "https://www.linkedin.com/posts/linkedin_add-job-preferences-activity-7208418413906464769-P2hn"
  ],
  "max_reposts": 100
}
```

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "post_urls": [
        "https://www.linkedin.com/posts/linkedin_add-job-preferences-activity-7208418413906464769-P2hn"
    ],
    "max_reposts": 100
};

// Run the Actor and wait for it to finish
const run = await client.actor("datadoping/linkedin-post-repost-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "post_urls": ["https://www.linkedin.com/posts/linkedin_add-job-preferences-activity-7208418413906464769-P2hn"],
    "max_reposts": 100,
}

# Run the Actor and wait for it to finish
run = client.actor("datadoping/linkedin-post-repost-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "post_urls": [
    "https://www.linkedin.com/posts/linkedin_add-job-preferences-activity-7208418413906464769-P2hn"
  ],
  "max_reposts": 100
}' |
apify call datadoping/linkedin-post-repost-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,datadoping/linkedin-post-repost-scraper"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/Lj0iRHPdGBeLEI3tu/builds/Sqwx6Ne80VvjksKLK/openapi.json