LinkedIn Profile Scraper

Turn a list of LinkedIn usernames or profile URLs into complete, structured public-profile records.

I built LinkedIn Profile Scraper for the point where opening profiles one by one stops being research and starts being repetitive work. Give it the people you already know you need; it returns consistent records that are easier to compare, filter, and pass into the next step of a recruiting, sales, or research workflow.

A profile reader for known people, not a search engine

This Actor starts from usernames or /in/ URLs. It is the right fit when discovery has already happened and the job is to collect the public context around each person: headline, location, about text, audience counts, work and education history, articles, activity, and related profiles when LinkedIn exposes them.

That boundary is deliberate. I would use the LinkedIn Jobs Scraper or Related User Scraper to discover candidates, then use this Actor to build the deeper profile dataset.

Give the run a clean list

Paste bare usernames or full public profile URLs into the same username field. Duplicates and URL formatting are normalized before profiles are processed, while maxItems gives you a simple brake for test runs.

Batch profile lookup

Enter one or more LinkedIn usernames or /in/ profile URLs and fetch the full public profile for each.

Field	Type	Required	Description
username	array	Yes	LinkedIn usernames or /in/ profile URLs to fetch full profile details for.
maxItems	integer	No	Maximum number of profiles to fetch. Set to 0 for no item limit.

A small input worth copying

{
  "username": [
    "williamhgates"
  ],
  "maxItems": 20
}

Read the result like a research record

The output is intentionally wider than a contact card. Identity and network fields help with sorting; history fields explain a person's background; content fields preserve the public material that can add context to an analysis.

Identity

Field	Type	Description
username	string	Username used to fetch this profile.
name	string	Name shown on the profile.
headline	string	Current headline or organization text shown on the profile.
location	string	Location shown on the profile.
country	string	Country code shown on the profile.
about	string	About/summary text shown on the profile.
url	string	LinkedIn profile URL.
image	string	Profile photo or company logo URL.

Network

Field	Type	Description
followers	number	Follower count.
connections	mixed	Connection count, when public.

History

Field	Type	Description
works_for	array	Current and past organizations, with start/end years.
experience	array	Work experience entries with title, company, and date range.
education	array	Education entries with school and date range.
education_jsonld	array	Structured education history (schema.org shape).
awards	array	Awards listed on the profile.
languages	array	Languages listed on the profile.

Content

Field	Type	Description
articles	array	LinkedIn Pulse articles published by the profile.
related_profiles	array	Related profile suggestions shown on the profile.
activity	array	Recent posts and articles shown on the profile or company page.
job_titles	array	Job titles shown across the profile's current positions.
badges	string	Creator or Top Voice badges shown on the profile.
jsonld	object	Structured schema.org data embedded in the page.

One shortened profile record

{
  "username": "williamhgates",
  "name": "Bill Gates",
  "headline": "Co-chair, Founder, Co-founder",
  "location": "Seattle, Washington, United States",
  "followers": 40509534,
  "url": "https://www.linkedin.com/in/williamhgates"
}

Public LinkedIn pages vary. A missing field normally means it was not visible on that profile at collection time, so downstream workflows should treat optional values as optional rather than inventing replacements.

Cost control without guesswork

This Actor uses Apify pay-per-result pricing. You are charged for successful dataset results according to the Actor pricing shown on the Apify Pricing tab. Enrichment may add extra billable events when enabled.

Apify's free credits may cover small test runs and up to the free result allowance configured for the Actor.

Start with a low maxItems value before enabling enrichment for large runs.

My practical recommendation is to test a handful of usernames first, inspect the dataset columns you care about, and only then increase maxItems for the larger batch.

Run the same profile job from code

Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_API_TOKEN")
run = client.actor("thenetaji/linkedin-profile-scraper").call(run_input={
    "username": [
        "williamhgates"
    ],
    "maxItems": 20
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

Node.js

import { ApifyClient } from "apify-client";

const client = new ApifyClient({ token: "YOUR_APIFY_API_TOKEN" });
const run = await client.actor("thenetaji/linkedin-profile-scraper").call({
  "username": [
    "williamhgates"
  ],
  "maxItems": 20
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Responsible use

This Actor extracts publicly available LinkedIn profile information. It should not be used to collect private account data, bypass access controls, or contact people in ways that violate privacy laws, LinkedIn terms, or your own compliance obligations. If you are unsure, consult a qualified lawyer.

Continue the LinkedIn workflow

• LinkedIn Company Scraper — Fetch full public LinkedIn company page details — industry, size, headquarters, specialties, similar and affiliated pages, and recent updates — for one or more company handles or URLs.
• LinkedIn Jobs Scraper — Search LinkedIn jobs by keyword and location with date, experience, job-type, and workplace filters, paginate through results, and optionally enrich each job with the full posting.
• LinkedIn Related User Scraper — Extract related LinkedIn profile suggestions from one or more seed profiles, with optional full profile enrichment for each related user.

Talk to the maintainer

Use the Issues tab on the Actor page for bug reports, missing fields, and feature requests.