# LinkedIn Post Engagers (Likers & Commenters) (`apt_marble/linkedin-post-engagers-likers-commenters`) Actor

Collect everyone who reacted to or commented on a LinkedIn post.

- **URL**: https://apify.com/apt_marble/linkedin-post-engagers-likers-commenters.md
- **Developed by:** [Hamza](https://apify.com/apt_marble) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.40 / 1,000 engager founds

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

## LinkedIn Post Engagers (Likers & Commenters)

Collect everyone who reacted to or commented on any LinkedIn post you can see: reactions with the reaction type, and comments with author, text, date and link. Includes multiple pages of comments and visible replies. Perfect for engagement-based lead lists ("everyone who liked this post") and influencer analytics.

### What you get

One dataset row per reaction or comment, with a **Type** column (`reaction` or `comment`):

| Field | Content |
|---|---|
| Type | `reaction` or `comment` |
| Image | Profile picture (thumbnail) |
| Name | Full name |
| Profile URL | Public profile link |
| Headline | Current role line |
| Reaction | Reaction type (reaction rows: LIKE, PRAISE, EMPATHY...) |
| Comment | Comment text (comment rows) |
| Date | Comment date (comment rows) |
| Comment URL | Direct link to the comment (comment rows) |

### Inputs

- **Post URL** - the full post link. Both forms work: `https://www.linkedin.com/posts/...` and `https://www.linkedin.com/feed/update/urn:li:activity:.../`.
- **Scrape reactions / Scrape comments** - turn each on or off.
- **Maximum results (per type)** - stop after this many reactions, and this many comments (1-1000 each). Comments and replies share the comments limit.

### Good to know

- **Steady pacing.** One request at a time, a randomized 1-4 second pause between requests, and the run stops immediately on any refusal or rate limit.

- **Visibility.** Only visible posts can be read. If a post is private or restricted, the run ends cleanly with an explanation.

- **Hidden profiles stay hidden.** If LinkedIn serves a reactor without identity, that row is skipped - no tool can reveal those names.

- **Maintenance.** LinkedIn changes from time to time. If a run reports that data could not be read, try again later or contact us through the Apify store page.

- **Comment coverage.** Comments use the order LinkedIn serves. Some replies may be hidden by its relevance filter. A partial-read notice means the saved comments are usable, but more may exist. Reaching your selected limit also stops collection.

### Example output

```json
{
  "type": "reaction",
  "image": "https://media.licdn.com/dms/image/.../profile.jpg",
  "name": "Jane Example",
  "profileUrl": "https://www.linkedin.com/in/jane-example",
  "headline": "Engineer at Example Corp",
  "reactionType": "LIKE",
  "commentText": null,
  "commentDate": null,
  "commentUrl": null
}
```

# Actor input Schema

## `postUrl` (type: `string`):

Full LinkedIn post link, e.g. https://www.linkedin.com/posts/linkedin_news-activity-7123456789012345678-ab12/ or https://www.linkedin.com/feed/update/urn:li:activity:7123456789012345678/

## `scrapeReactions` (type: `boolean`):

Collect everyone who reacted to the post, with the reaction type (like, celebrate, support...).

## `scrapeComments` (type: `boolean`):

Collect the post's comments with author, text, date and link.

## `maxResults` (type: `integer`):

Stop after this many reactions, and this many comments (1-1000 each).

## Actor input object example

```json
{
  "postUrl": "https://www.linkedin.com/feed/update/urn:li:activity:7123456789012345678/",
  "scrapeReactions": true,
  "scrapeComments": true,
  "maxResults": 100
}
```

# Actor output Schema

## `engagers` (type: `string`):

Dataset with one row per reactor or commenter.

# 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 = {
    "postUrl": "https://www.linkedin.com/feed/update/urn:li:activity:7123456789012345678/",
    "scrapeReactions": true,
    "scrapeComments": true,
    "maxResults": 100
};

// Run the Actor and wait for it to finish
const run = await client.actor("apt_marble/linkedin-post-engagers-likers-commenters").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 = {
    "postUrl": "https://www.linkedin.com/feed/update/urn:li:activity:7123456789012345678/",
    "scrapeReactions": True,
    "scrapeComments": True,
    "maxResults": 100,
}

# Run the Actor and wait for it to finish
run = client.actor("apt_marble/linkedin-post-engagers-likers-commenters").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 '{
  "postUrl": "https://www.linkedin.com/feed/update/urn:li:activity:7123456789012345678/",
  "scrapeReactions": true,
  "scrapeComments": true,
  "maxResults": 100
}' |
apify call apt_marble/linkedin-post-engagers-likers-commenters --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,apt_marble/linkedin-post-engagers-likers-commenters"
        }
    }
}
```

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/houxI7pq7dBOvpdBm/builds/xqj2FrHklT15DvNOT/openapi.json