# LinkedIn Brand Mention Monitoring

**Use case:** 

Stay updated on how key brands like Google, Apify, and Facebook are discussed on LinkedIn. This task collects posts mentioning these brands, providing insights into engagement and trends. Analyze the sentiment and impact of mentions to keep your finger on the pulse of brand conversations in professional contexts.

## Input

```json
{
  "query": [
    "Google",
    "Apify",
    "Facebook"
  ],
  "excludeWords": "course webinar",
  "country": [
    "us",
    "gb"
  ],
  "hashtags": [
    "hiring",
    "ai"
  ],
  "contentType": "POST",
  "hasComments": "",
  "isHiring": "",
  "hasLink": "",
  "postedWithinHours": 48,
  "timeRelevance": "",
  "postedAfter": "2026-09-01T00:00:00Z",
  "postedBefore": "2026-09-05T00:00:00Z",
  "parsedWithinHours": 24,
  "parsedAfter": "2026-09-01T00:00:00Z",
  "parsedBefore": "2026-09-02T00:00:00Z",
  "authorType": "any",
  "sortBy": "newest",
  "limit": 25,
  "offset": 0
}
```

## Output

```json
{
  "postKey": {
    "label": "Post Key",
    "format": "text"
  },
  "text": {
    "label": "Text",
    "format": "text"
  },
  "hashtags": {
    "label": "Hashtags",
    "format": "text"
  },
  "contentType": {
    "label": "Content Type",
    "format": "text"
  },
  "author": {
    "label": "Author",
    "format": "text"
  },
  "authorUrl": {
    "label": "Author URL",
    "format": "link"
  },
  "authorType": {
    "label": "Author Type",
    "format": "text"
  },
  "createdAt": {
    "label": "Posted At",
    "format": "text"
  },
  "geo": {
    "label": "Geo",
    "format": "text"
  },
  "likes": {
    "label": "Likes",
    "format": "number"
  },
  "commentsCount": {
    "label": "Comments",
    "format": "number"
  },
  "hasLink": {
    "label": "Has Link?",
    "format": "boolean"
  },
  "isHiring": {
    "label": "Hiring?",
    "format": "boolean"
  },
  "likesPerHour": {
    "label": "Likes / Hour",
    "format": "number"
  },
  "commentsPerHour": {
    "label": "Comments / Hour",
    "format": "number"
  },
  "postUrl": {
    "label": "Post URL",
    "format": "link"
  },
  "comments": {
    "label": "Parsed Comments",
    "format": "text"
  }
}
```

## How it works

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

The LinkedIn Posts Search - Bulk, Hiring, Country& Comments search Actor is ready to run with the inputs already set for "LinkedIn Brand Mention Monitoring". [Sign up or log in](https://console.apify.com/create-task-from-example/9tvucujvg5mytS2dy) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "LinkedIn Brand Mention Monitoring" task

The LinkedIn Posts Search - Bulk, Hiring, Country& Comments search Actor will start running based on the input automatically. You can also change all the input fields, like search queries, exclude words, and more, to match your specific use case.

### 3. Receive the "LinkedIn Brand Mention Monitoring" 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 key, text, hashtags, 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 "LinkedIn Brand Mention Monitoring" task via API](https://apify.com/sandhive/linkedin-posts-parser.md).

## About this Actor

This example demonstrates how to use [LinkedIn Posts Search - Bulk, Hiring, Country& Comments search](https://apify.com/sandhive/linkedin-posts-parser.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/sandhive/linkedin-posts-parser.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/sandhive/linkedin-posts-parser.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`).