Introducing 4 New LinkedIn Post Endpoints: Full Post Analytics via API

Introduction

Until now, Datamagnet's API focused on people and company data. Today, we're expanding into LinkedIn post analytics with 4 new endpoints that let you extract everything about a LinkedIn post—from the full post content to every comment, reaction, and repost.

Whether you're building a social listening dashboard, tracking content performance for clients, or analyzing engagement patterns at scale, these endpoints give you the raw data you need.

All you need is a LinkedIn post URL. We handle extracting the activity ID, calling the right upstream APIs, and returning clean, paginated, snake_case JSON.

What's New

Here's a quick overview of the 4 new endpoints:

| Endpoint | What It Does | Cost | |---|---|---| | POST /api/v1/linkedin/post | Full post details, author, social counts | 5 credits | | POST /api/v1/linkedin/post/comments | Paginated comments with commenter profiles | 5 credits | | POST /api/v1/linkedin/post/reactions | Who reacted and reaction types (Like, Praise, etc.) | 5 credits | | POST /api/v1/linkedin/post/reposts | Who reposted, with commentary and reshare info | 5 credits |

All endpoints accept a simple JSON body:

{
  "url": "https://www.linkedin.com/posts/username_slug-activity-7430615551086850048-XXXX"
}

We support every common LinkedIn post URL format—whether it's a /posts/ share link, a /feed/update/ link, or a ugcPost URL. The API auto-extracts the activity ID for you.

1. Post Details

Endpoint: POST /api/v1/linkedin/post

This is your starting point. Given any LinkedIn post URL, it returns the complete post data in a single call:

Post content — full text, posted timestamp, and the post's URN
Author info — name, headline, profile picture, and profile link
Social counts — total likes, comments, shares, and a reaction-type breakdown (e.g., 108 Likes, 10 Praise, 4 Empathy)
Article attachments — title, subtitle, link, and thumbnail for shared articles
Repost metadata — if the post is a repost, you get the original post header and who reposted it
Related URNs — the reactions_urn, comments_urn, and reposts_urn you can use with the other endpoints

import requests

response = requests.post(
    "https://api.datamagnet.co/api/v1/linkedin/post",
    json={"url": "https://www.linkedin.com/feed/update/urn:li:activity:7219434359085252608"},
    headers={"Authorization": "Bearer YOUR_API_KEY"}
)

data = response.json()
print(data["message"]["post_text"])
print(f"Likes: {data['message']['social_count']['num_likes']}")

2. Post Comments

Endpoint: POST /api/v1/linkedin/post/comments

Retrieve every comment on a post with full commenter profiles. Supports cursor-based pagination to walk through all comments.

Each comment includes:

Comment text and permalink
Commenter name, headline, and profile picture
Whether the comment is pinned or edited
Reaction breakdown on the comment itself
Reply count and top replies

page = 1
all_comments = []

while page is not None:
    response = requests.post(
        "https://api.datamagnet.co/api/v1/linkedin/post/comments",
        json={
            "url": "https://www.linkedin.com/posts/...",
            "page": page
        },
        headers={"Authorization": "Bearer YOUR_API_KEY"}
    )

    data = response.json()
    all_comments.extend(data["message"]["comments"])
    page = data.get("cursor")

print(f"Total comments: {len(all_comments)}")

The cursor field returns the next page number. When it's null, you've reached the end.

3. Post Reactions

Endpoint: POST /api/v1/linkedin/post/reactions

See exactly who reacted to a post and what type of reaction they gave. LinkedIn supports 6 reaction types:

👍 Like
👏 Praise (Celebrate)
❤️ Empathy (Love)
💡 Interest (Insightful)
🙏 Appreciation (Support)
😄 Entertainment (Funny)

Each reaction record includes the person's name, headline, profile URL, profile picture, and the specific reaction type. Paginated the same way as comments.

response = requests.post(
    "https://api.datamagnet.co/api/v1/linkedin/post/reactions",
    json={
        "url": "https://www.linkedin.com/posts/...",
        "page": 1
    },
    headers={"Authorization": "Bearer YOUR_API_KEY"}
)

data = response.json()
for reaction in data["message"]["reactions"]:
    print(f"{reaction['title']} — {reaction['reaction_type']}")

4. Post Reposts

Endpoint: POST /api/v1/linkedin/post/reposts

Track how content spreads across LinkedIn. This endpoint returns everyone who reposted a specific post, including:

Direct reposts — the reposter's name, headline, profile picture, and any commentary they added
Reshares — when someone reposted a repost, you get a nested header showing the chain (e.g., "Michael Chen reposted this")
Company reposts — when a company page reshares, you get the company name, logo, and follower count

response = requests.post(
    "https://api.datamagnet.co/api/v1/linkedin/post/reposts",
    json={
        "url": "https://www.linkedin.com/posts/...",
        "page": 1
    },
    headers={"Authorization": "Bearer YOUR_API_KEY"}
)

Design Decisions

A few things worth highlighting about how we built these:

Snake case everywhere. All response keys are in snake_case, even though LinkedIn's internal API uses camelCase. We convert everything automatically so your Python and Ruby code looks idiomatic without post-processing.

Consistent pagination. Every paginated endpoint uses the same pattern: pass page in the request body, read cursor from the response. When cursor is null, you're done. No offset math required.

Any URL format. We auto-detect and extract activity IDs from multiple LinkedIn URL formats — /posts/ share links, /feed/update/ links, ugcPost URLs, and more. Just paste whatever URL you have.