Extract LinkedIn Post Likers

LinkedIn Post Likers Extractor extracts the LinkedIn profiles of individuals who liked a specific post.

Edges is not related to LinkedIn and is not an official LinkedIn product.

API Endpoint

POST/v1/actions/linkedin-extract-post-likers/run/live

Parameters

Request parameters

Input Parameters

Integration Parameters

Guide

What Extract LinkedIn Post Likers does

Extract LinkedIn Post Likers returns the LinkedIn profiles of every user who reacted to a specific post, as a structured dataset. You get each liker with profile metadata and the reaction type they left, turning a like count into an addressable list.

The action runs on the LinkedIn level and is one of the most common primitives used by revenue teams to convert organic engagement into pipeline.

How it works

You pass a LinkedIn post URL, Edges reads the reactions panel through your authenticated LinkedIn session, and it paginates through every liker. Each row includes the reaction type (like, celebrate, support, love, insightful, funny) so you can segment quality of signal.

Runs execute on Edges infrastructure with safe rate pacing. Viral posts with tens of thousands of likes should run async so pagination completes without timing out.

When to use Extract LinkedIn Post Likers

Reach for Extract LinkedIn Post Likers whenever a post is a proxy for topical interest — yours, a competitor's, or a category influencer's. It maps to the LinkedIn search API use case.

It is the cleanest primitive for "who should I talk to this week?" — a single viral post in your category can produce hundreds of ICP-fit leads in one run.

Use cases

  • Warm lead generation. Convert likers on your own posts into a pipelineable list segmented by title and company.
  • Competitor displacement. Extract likers on a competitor's launch post and target the subset at accounts you cover.
  • Influencer-led ABM. When a category influencer posts about a pain you solve, extract their likers and route matches to AEs.
  • Event targeting. Invite likers from the last 30 days of your best posts to an upcoming webinar.
  • Product launch audience. Build an outreach list from likers of a relevant launch post for your next announcement.

Best practices

  • Weight reactions. insightful and support typically indicate stronger interest than a generic like. Weight accordingly in your scoring.
  • Enrich before CRM sync. Pair with Extract LinkedIn Profile to hydrate rows with experience and skills before you push to Salesforce or HubSpot.
  • Run async for viral posts. Posts with 10k+ reactions should run async so Edges can paginate politely.
  • Dedupe across campaigns. Use publicProfileUrl as the canonical key to avoid contacting the same liker from multiple posts.

Common questions

How many likers can I extract per run?

Edges paginates the full list. For very large posts, run Extract LinkedIn Post Likers async so the job completes in the background instead of one long-lived HTTP call.

Does Extract LinkedIn Post Likers use my LinkedIn account or a shared pool?

Your LinkedIn account. The reactions panel is read through your authenticated LinkedIn session on Edges, and visibility matches your manual view.

Can I chain Extract LinkedIn Post Likers with other Edges actions?

Yes. Common patterns are Extract LinkedIn Post Likers into Extract LinkedIn Post Commenters for a full engagement set, or into Message LinkedIn Profile for referenced outreach.

Get started

Run Extract LinkedIn Post Likers from the Edges library, schedule it against your best-performing posts, or call it from the Edges API. Browse the full Actions library for engagement primitives you can chain into your CRM sync.

Code Examples

bash
curl -X POST "https://api.edges.run/v1/actions/linkedin-extract-post-likers/run/live" \
  -H "X-API-KEY: <YOUR_API_KEY>" \
  -H "Content-Type: application/json" \
  -d '{
  "identity_ids": [
    "your-identity-uuid"
  ],
  "identity_mode": "direct",
  "input": {
    "linkedin_post_url": "https://www.linkedin.com/in/example-profile",
    "custom_data": "example_value"
  }
}'

Output Example

[
  {
    "full_name": "John Doe",
    "first_name": "John",
    "last_name": "Doe",
    "reaction_type": "example_value",
    "reaction_urn": "example_value",
    "linkedin_profile_url": "https://www.linkedin.com/in/example-profile",
    "liker_connection_degree": "example_value",
    "sales_navigator_profile_id": "example-123",
    "sales_navigator_profile_url": "https://www.linkedin.com/in/example-profile",
    "job_title": "Software Engineer at Example Corp",
    "linkedin_profile_id": 42,
    "linkedin_people_post_search_url": "https://www.linkedin.com/in/example-profile",
    "linkedin_post_url": "https://www.linkedin.com/in/example-profile",
    "linkedin_post_id": "example-123"
  }
]

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