# Collect LinkedIn applicant counts for recruiting research

**Use case:** 

Collect available applicant text, parsed counts, posting dates and job titles from selected LinkedIn listings for recruiting research. Keep the original applicant wording when comparing records: phrases such as over 100 are not exact applicant totals, and missing values may default to zero.

## Input

```json
{
  "inputList": [
    "https://www.linkedin.com/jobs/view/4378357766/"
  ]
}
```

## Output

```json
{
  "input": {
    "label": "Input",
    "format": "string"
  },
  "status": {
    "label": "Status",
    "format": "string"
  },
  "id": {
    "label": "ID",
    "format": "string"
  },
  "url": {
    "label": "URL",
    "format": "string"
  },
  "title": {
    "label": "Title",
    "format": "string"
  },
  "company.id": {
    "label": "Company / ID",
    "format": "text"
  },
  "company.name": {
    "label": "Company / Name",
    "format": "text"
  },
  "company.url": {
    "label": "Company / URL",
    "format": "link"
  },
  "company.logo": {
    "label": "Company / Logo",
    "format": "image"
  },
  "location": {
    "label": "Location",
    "format": "string"
  },
  "address.street": {
    "label": "Address / Street",
    "format": "text"
  },
  "address.city": {
    "label": "Address / City",
    "format": "text"
  },
  "address.region": {
    "label": "Address / Region",
    "format": "text"
  },
  "address.postal_code": {
    "label": "Address / Postal Code",
    "format": "text"
  },
  "address.country": {
    "label": "Address / Country",
    "format": "text"
  },
  "workplace_type": {
    "label": "Workplace Type",
    "format": "string"
  },
  "description": {
    "label": "Description",
    "format": "string"
  },
  "description_html": {
    "label": "Description Html",
    "format": "string"
  },
  "posted_at": {
    "label": "Posted At",
    "format": "string"
  },
  "posted_time": {
    "label": "Posted Time",
    "format": "string"
  },
  "valid_through": {
    "label": "Valid Through",
    "format": "string"
  },
  "applicants_text": {
    "label": "Applicants Text",
    "format": "string"
  },
  "applicants": {
    "label": "Applicants",
    "format": "integer"
  },
  "job_status": {
    "label": "Job Status",
    "format": "string"
  },
  "apply_url": {
    "label": "Apply URL",
    "format": "string"
  },
  "seniority_level": {
    "label": "Seniority Level",
    "format": "string"
  },
  "employment_type": {
    "label": "Employment Type",
    "format": "string"
  },
  "job_function": {
    "label": "Job Function",
    "format": "string"
  },
  "industries": {
    "label": "Industries",
    "format": "string"
  },
  "qualifications": {
    "label": "Qualifications",
    "format": "string"
  },
  "skills": {
    "label": "Skills",
    "format": "array"
  },
  "benefits": {
    "label": "Benefits",
    "format": "array"
  },
  "salary.currency": {
    "label": "Salary / Currency",
    "format": "text"
  },
  "salary.value": {
    "label": "Salary / Value",
    "format": "number"
  },
  "salary.min": {
    "label": "Salary / Min",
    "format": "number"
  },
  "salary.max": {
    "label": "Salary / Max",
    "format": "number"
  },
  "salary.unit": {
    "label": "Salary / Unit",
    "format": "text"
  },
  "criteria.name": {
    "label": "Criteria / Name",
    "format": "array"
  },
  "criteria.value": {
    "label": "Criteria / Value",
    "format": "array"
  }
}
```

## About this Actor

This example demonstrates how to use [LinkedIn Job Details Scraper – Descriptions & Data](https://apify.com/scrapingmonkey/linkedin-job-details-scraper.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/scrapingmonkey/linkedin-job-details-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/scrapingmonkey/linkedin-job-details-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`).