# Profile Reactions Scraper for LinkedIn \[No Cookies] (`apimaestro/linkedin-profile-reactions`) Actor

Linkedin User Reactions Scraper:
Extract reactions for LinkedIn profiles and users including post content, reactions, stats, article, media attachments and more.

- **URL**: https://apify.com/apimaestro/linkedin-profile-reactions.md
- **Developed by:** [API Maestro](https://apify.com/apimaestro) (community)
- **Categories:** Social media, Developer tools
- **Stats:** 1,070 total users, 107 monthly users, 100.0% runs succeeded, 40 bookmarks
- **User rating**: 5.00 out of 5 stars

## Pricing

$5.00 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

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

### 🚀 LinkedIn Profile Reactions Scraper

Extract public Reactions made by Linkedin User. Get structured data including articles and posts

#### For other LinkedIn actors, check: https://apify.com/apimaestro

### ✨ Key Features

- No account needed:  Don't risk your account security by sharing your cookies and don't get your account restricted or banned!
- Recent Reactions
- Post content and media
- Reaction counts by type (likes, comments, etc.)
- Post URLs for sharing
- Media attachments (images, articles, etc.)
- Pagination support for older posts

### 🔧 Simple Usage

Provide a single or multiple LinkedIn profile usernames to get their recent reactions and activities. The username is the last part of a LinkedIn profile URL (e.g., 'satyanadella' from linkedin.com/in/satyanadella).

### 📊 Result Limits

Each profile can return up to 3000 reactions. Use the `limit` parameter to control the maximum number of reactions per profile:

- Default: 100 reactions per profile
- Minimum: 1 reaction per profile
- Maximum: 100 reactions per profile

### Output Preview

```json
{
        },
        "reactions": [
            {
                "action": "...",
                "text": "...",
                "author": {
                    "firstName": "...",
                    "lastName": "..",
                    "headline": "...",
                    "profile_url": "...":,
                    "profile_picture": "..."
                },
                "post_stats": {
                    "totalReactionCount": 1177,
                    "like": 884,
                    "appreciation": 3,
                    "empathy": 103,
                    "interest": 22,
                    "praise": 165,
                    "comments": 54,
                    "reposts": 61
                },
                "timestamps": {
                    "relative": "5d"
                },
        ],
    "metadata": {
        "pagination_token": "dXJuOmxpOmFj..."
    }
}
```

<br>

***

**Disclaimer:** This Actor is an independent tool and is not affiliated with, endorsed by, or sponsored by LinkedIn Corporation. LinkedIn® is a registered trademark of LinkedIn Corporation. All trademarks are property of their respective owners.

# Actor input Schema

## `usernames` (type: `array`):

List of LinkedIn profile identifiers. You can use either:

- Usernames (e.g., 'satyanadella')
- Profile URLs (e.g., 'https://www.linkedin.com/in/satyanadella')
- Comma-separated values will be split automatically

## `limit` (type: `integer`):

Maximum number of reactions to extract per profile (1-3000). Default is 100 reactions per profile

## Actor input object example

```json
{
  "usernames": [
    "satyanadella",
    "https://www.linkedin.com/in/williamhgates/"
  ],
  "limit": 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 = {
    "usernames": [
        "satyanadella",
        "https://www.linkedin.com/in/williamhgates/"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("apimaestro/linkedin-profile-reactions").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 = { "usernames": [
        "satyanadella",
        "https://www.linkedin.com/in/williamhgates/",
    ] }

# Run the Actor and wait for it to finish
run = client.actor("apimaestro/linkedin-profile-reactions").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 '{
  "usernames": [
    "satyanadella",
    "https://www.linkedin.com/in/williamhgates/"
  ]
}' |
apify call apimaestro/linkedin-profile-reactions --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,apimaestro/linkedin-profile-reactions"
        }
    }
}

```

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/FNhKFjeL8hWQtMeZI/builds/2fnoAtambaweJ9qmt/openapi.json