# Export Comments From LinkedIn Posts

**Use case:** 

Scrapes visible comments and engagement details from public LinkedIn posts without logging in or using browser extensions. Built for growth marketers and social media teams tracking engagement campaigns, it returns comments with authorName, text, postedAt, and reactionsCount, alongside post content and commentsCount. Change postUrl to target any public LinkedIn post.

## Input

```json
{
  "mode": "postUrls",
  "profileUrl": "https://www.linkedin.com/in/satyanadella",
  "postUrl": "https://www.linkedin.com/posts/nvidia_ai-is-technology-that-is-built-and-improved-activity-7508569677040893954-sffp",
  "maxPosts": 1,
  "postedLimit": "",
  "maxComments": 10,
  "includeVideoTranscript": false,
  "scrapeInteractors": false,
  "scrapeReactions": false,
  "maxInteractors": 50,
  "language": "en",
  "includeReposts": true,
  "minReactions": 0,
  "minComments": 0,
  "mediaTypes": []
}
```

## Output

```json
{
  "postId": {
    "label": "Post ID",
    "format": "text"
  },
  "authorName": {
    "label": "Author",
    "format": "text"
  },
  "authorFollowers": {
    "label": "Author Followers",
    "format": "number"
  },
  "authorHeadline": {
    "label": "Headline",
    "format": "text"
  },
  "authorProfileUrl": {
    "label": "Author URL",
    "format": "link"
  },
  "postedAt": {
    "label": "Posted At",
    "format": "text"
  },
  "content": {
    "label": "Post Content",
    "format": "text"
  },
  "mediaType": {
    "label": "Media Type",
    "format": "text"
  },
  "reactionsCount": {
    "label": "Reactions",
    "format": "number"
  },
  "commentsCount": {
    "label": "Comments",
    "format": "number"
  },
  "comments": {
    "label": "Top Comments",
    "format": "text"
  },
  "videoDuration": {
    "label": "Video Duration",
    "format": "text"
  },
  "postUrl": {
    "label": "Post URL",
    "format": "link"
  },
  "inputUrl": {
    "label": "Input URL",
    "format": "text"
  },
  "scrapedAt": {
    "label": "Scraped At",
    "format": "text"
  }
}
```

## How it works

### 1. Sign up on Apify or log in

The LinkedIn Profile Feed Scraper with Likers & Commenters Actor is ready to run with the inputs already set for "Export Comments From LinkedIn Posts". [Sign up or log in](https://console.apify.com/create-task-from-example/ASNgGi0jefDacNg1H) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "Export Comments From LinkedIn Posts" task

The LinkedIn Profile Feed Scraper with Likers & Commenters Actor will start running based on the input automatically. You can also change all the input fields, like mode, profile url, and more, to match your specific use case.

### 3. Receive the "Export Comments From LinkedIn Posts" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as post id, author, author followers, and more.

### 4. Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also [run the "Export Comments From LinkedIn Posts" task via API](https://apify.com/vexaloom-labs/linkedin-profile-feed-scraper-with-likers.md).

## About this Actor

This example demonstrates how to use [LinkedIn Profile Feed Scraper with Likers & Commenters](https://apify.com/vexaloom-labs/linkedin-profile-feed-scraper-with-likers.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/vexaloom-labs/linkedin-profile-feed-scraper-with-likers.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

This Task's input is already configured above. Use it as-is rather than inventing a new one.

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 full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/vexaloom-labs/linkedin-profile-feed-scraper-with-likers.md

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`).