# Linkedin Profile Comments Scraper (No Cookie) (`datadoping/linkedin-profile-comments-scraper`) Actor

For just $1.2 per 1,000 comments, scrape comments made by a profile from activity on LinkedIn. It Scrapes text, reactions, pinned, timestamp, etc.
Note: If you're on free tier you can only scrape 4 profile and 100 comments per profile per run (12 profiles in total)

- **URL**: https://apify.com/datadoping/linkedin-profile-comments-scraper.md
- **Developed by:** [Data Doping](https://apify.com/datadoping) (community)
- **Categories:** Social media, Lead generation, Automation
- **Features:** Limited permissions
- **Stats:** 323 total users, 94 monthly users, 100.0% runs succeeded, 7 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.20 / 1,000 comments

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?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

🔍 What is LinkedIn Profile Comments Scraper?

LinkedIn Profile Comments Scraper automates the process of gathering publicly available comments from LinkedIn profiles. Simply provide one or more LinkedIn usernames or profile URLs, and the scraper will fetch comprehensive comment details such as:

**Comment Content:**

- Comment text and content
- Comment URLs and timestamps
- Commenter information (name, headline, profile picture)
- Comment statistics (likes, replies, reactions)

**Post Context:**

- Post images with URLs
- Post author information
- Post content references

**Engagement Data:**

- Total reaction counts
- Individual reaction types (like, appreciation, empathy, interest, praise)
- Reply counts
- Comment timestamps (both absolute and relative)
- Pinned comment status

**Pagination Support:**

- Automatic pagination handling
- Configurable maximum comments per profile
- Efficient data collection with rate limiting

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

💡 Why Scrape LinkedIn Profile Comments?

LinkedIn comments provide valuable insights for professionals and businesses:

🔎 **Engagement Analysis**: Analyze what types of comments generate the most engagement and responses.

🧠 **Community Insights**: Understand community sentiment and discussion patterns around specific topics.

📈 **Social Listening**: Monitor conversations and reactions to industry content and trends.

🤝 **Relationship Building**: Identify active community members and potential networking opportunities.

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

🎯 **Brand Monitoring**: Track mentions and sentiment around your brand or industry topics.

⚖️ Is it Legal to Scrape LinkedIn Comments?

We prioritize ethical scraping practices.

This scraper only extracts information that users have chosen to display publicly on their LinkedIn profiles. 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 usernames or full profile URLs
   - Username: `example-user`
   - URL: `https://linkedin.com/in/example-user`
   - URL: `linkedin.com/in/example-user`

2. **Comments Limit**: Set maximum number of comments to scrape per profile (minimum 10)

3. **Rate Limits**: The scraper respects LinkedIn's rate limits with 30 requests per minute

4. **Error Handling**: Invalid usernames, company profiles, or malformed URLs will be logged as errors in the dataset

5. **Freemium Limits**: Free users are limited to 4 profiles per run with maximum 100 comments per profile

📊 Output Data Structure

The scraper returns comprehensive comment data including:

- **Comment Content**: Text, URLs, timestamps, and metadata
- **Commenter Info**: Name, headline, profile picture, and profile URL
- **Engagement**: Reaction counts, replies, and interaction data
- **Post Context**: Post images, post author information, and post content
- **Pagination**: Page numbers and pagination tokens for data organization

🔧 Technical Features

- **URL Processing**: Automatically converts LinkedIn URLs to usernames
- **Input Validation**: Validates usernames and detects company profiles
- **Pagination Handling**: Automatic pagination with configurable limits
- **Error Handling**: Comprehensive error reporting for failed requests
- **Rate Limiting**: Built-in delays to respect API limits
- **Resume Capability**: Can resume interrupted scraping sessions
- **Concurrent Processing**: Multiple workers for efficient data collection

⚠️ Important Notes

- Only personal LinkedIn profiles are supported (company pages will return errors)
- All data is publicly available information only
- Respects LinkedIn's terms of service and rate limits
- Free tier limited to 4 profiles per run with maximum 100 comments per profile
- Premium users have no limits
- Minimum 10 comments per profile (configurable maximum)

# Actor input Schema

## `profiles` (type: `array`):

List of LinkedIn usernames or profile URLs to scrape comments from. Enter one username/URL per line. URLs will be automatically converted to usernames.

## `max_comments` (type: `integer`):

Maximum number of comments to scrape from each profile. Minimum is 10 comments. Default is 10.

## Actor input object example

```json
{
  "profiles": [
    "aviv-tal-75b81"
  ],
  "max_comments": 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 = {
    "profiles": [
        "aviv-tal-75b81"
    ],
    "max_comments": 100
};

// Run the Actor and wait for it to finish
const run = await client.actor("datadoping/linkedin-profile-comments-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 = {
    "profiles": ["aviv-tal-75b81"],
    "max_comments": 100,
}

# Run the Actor and wait for it to finish
run = client.actor("datadoping/linkedin-profile-comments-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 '{
  "profiles": [
    "aviv-tal-75b81"
  ],
  "max_comments": 100
}' |
apify call datadoping/linkedin-profile-comments-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,datadoping/linkedin-profile-comments-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/YCvfCJb5szYvEUsvs/builds/3Vy4MnMTFJ7nVEzyP/openapi.json