# Review Satya Nadella’s LinkedIn Posts

**Use case:** 

Review Satya Nadella’s recent public LinkedIn posts and reposts for executive messaging and content strategy research. Each activity includes the post text, author, permalink, reaction total, and comment total. Change activityTypes to collect comments or reactions instead.

## Input

```json
{
  "profileUrls": [
    "https://www.linkedin.com/in/satyanadella/"
  ],
  "activityTypes": [
    "posts"
  ],
  "includePostDetails": true,
  "minDate": "",
  "maxDate": "",
  "maxActivitiesPerProfile": 50,
  "maxItems": 1
}
```

## Output

```json
{
  "activityType": {
    "label": "Type",
    "format": "text"
  },
  "profileName": {
    "label": "Profile",
    "format": "text"
  },
  "activityTimeAgo": {
    "label": "Activity Age",
    "format": "text"
  },
  "originalPostTimeAgo": {
    "label": "Post Age",
    "format": "text"
  },
  "originalAuthorName": {
    "label": "Post Author",
    "format": "text"
  },
  "content": {
    "label": "Content",
    "format": "text"
  },
  "reactionsCount": {
    "label": "Reactions",
    "format": "number"
  },
  "commentsCount": {
    "label": "Comments",
    "format": "number"
  },
  "originalPostPermalink": {
    "label": "Post URL",
    "format": "link"
  },
  "inputProfileUrl": {
    "label": "Profile URL",
    "format": "link"
  }
}
```

## How it works

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

The LinkedIn Profile Engagement Timeline Scraper Actor is ready to run with the inputs already set for "Review Satya Nadella’s LinkedIn Posts". [Sign up or log in](https://console.apify.com/create-task-from-example/FSZslK75T7qWWOAj0) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "Review Satya Nadella’s LinkedIn Posts" task

The LinkedIn Profile Engagement Timeline Scraper Actor will start running based on the input automatically. You can also change all the input fields, like profile urls, activity types, and more, to match your specific use case.

### 3. Receive the "Review Satya Nadella’s 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 type, profile, activity age, 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 "Review Satya Nadella’s LinkedIn Posts" task via API](https://apify.com/dataspryva/linkedin-profile-engagement-timeline-scraper.md).

## About this Actor

This example demonstrates how to use [LinkedIn Profile Engagement Timeline Scraper](https://apify.com/dataspryva/linkedin-profile-engagement-timeline-scraper.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/dataspryva/linkedin-profile-engagement-timeline-scraper.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/dataspryva/linkedin-profile-engagement-timeline-scraper.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`).