Who's Engaging With a LinkedIn Post or Profile? Reactions and Comments Explained

"Engagement" on LinkedIn gets treated as one number — likes plus comments, stacked under a post. It's actually two different questions with two different answers. Who reacted to this specific post? And, separately, what has this specific person been reacting to and commenting on lately, across everything they've touched on the platform? The first tells you who's paying attention to one thing you published. The second tells you what someone cares about right now, whether or not they ever saw your post.

Mindcase has four endpoints that split cleanly along that line: two work from a post URL outward (who engaged with it), two work from a profile URL outward (what that person has been engaging with). Knowing which direction you're pulling from changes what the data can actually tell you.

If you're an agent (or building one) reading this rather than a human, the full machine-readable schema for every endpoint below lives at mindcase.co/skills.md.

What's the difference between post-level and profile-level engagement?

Post-level data starts from a post URL and returns everyone who reacted or commented on it. Profile-level data starts from a person's profile URL and returns everything they've reacted to or commented on elsewhere — other people's posts, other companies' posts, wherever they've been active.

That distinction matters because the two answer opposite questions. If you already published something and want to know who noticed, you want post-level data. If you have a specific person — a lead, a prospect, a warm intro — and want to know what they're currently paying attention to on LinkedIn, post-level data can't help, because you don't know which posts to check. Profile-level data solves that: point it at the person, not the post.

What does a reaction actually tell you?

Post Reactions takes a post URL and returns everyone who reacted to it — 10 fields per row, including reactorName, reactorHeadline, reactorLocation, and reactionType. That last field is the real signal: LinkedIn splits reactions into six types (LIKE, PRAISE, EMPATHY, APPRECIATION, INTEREST, ENTERTAINMENT), and reactionTypeFilter lets you pull just one — INTEREST reads very differently from LIKE when you're trying to find people who'd actually want a follow-up conversation, not just people scrolling past.

Profile Reactions runs the same mechanic in reverse: point it at a person's profile URL and it returns what they've reacted to, with a single reaction field per row rather than a filterable type, alongside the full post they reacted to — postText, postAuthor, postAuthorHeadline, postDate. There's no reactionTypeFilter on this endpoint, so you get every reaction type back and filter client-side if you need to isolate one.

What does a comment give you that a reaction doesn't?

A reaction is binary — someone engaged, or they didn't. A comment has content. Post Comments returns 16 fields per comment on a given post, including the comment text itself, commenterHeadline, commenterFollowers, and isAuthor — whether the commenter is the original poster replying in their own thread, which matters if you're trying to separate genuine outside engagement from the poster managing their own comment section.

Profile Comments is the richer of the four endpoints — 27 fields — because pulling a person's comment history means also returning context on every post they commented on: postAuthor, postAuthorHeadline, postText, postReactions, postComments, postShares. It also returns onOwnPost, flagging comments someone left under their own posts the same way isAuthor does on the post-level endpoint, and commentReplies, the reply count each of their comments picked up.

How do you pull this data?

Say you want to find out who's actually engaged, versus who's just scrolling — starting from a post you already published.

How do you get everyone who reacted to a post?

curl -X POST "https://api.mindcase.co/v1/data/linkedin/post-reactions/run?wait=true" \
-H "Authorization: Bearer $MINDCASE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
  "params": {
    "posts": "linkedin.com/posts/example-post-id",
    "maxResults": 200,
    "reactionTypeFilter": ["INTEREST", "PRAISE"]
  }
}'

# $0.002 per reaction

Filtering to INTEREST and PRAISE up front, instead of pulling every LIKE too, is the difference between a list of 400 reactors and a list of 40 people worth a follow-up.

How do you check what a specific person has been engaging with?

curl -X POST "https://api.mindcase.co/v1/data/linkedin/profile-comments/run?wait=true" \
-H "Authorization: Bearer $MINDCASE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
  "params": {
    "profiles": "linkedin.com/in/example-profile",
    "maxResults": 50,
    "postedLimit": "month"
  }
}'

# $0.002 per comment

Each row comes back with the comment text plus which post it was left on and who wrote that post — enough to see not just that someone's active, but what topics and whose content they've been responding to over the last month.

What can't you get from Mindcase?

Two cases.

Private engagement stays private. All four endpoints only return reactions and comments visible on public posts and public profiles. A reaction on a post shared to a private group, or a comment from someone whose activity isn't public, won't show up — the same limit that applies to anyone viewing LinkedIn without a connection to that person.

Profile-level pulls are bounded by postedLimit, not a full history. linkedin/profile-reactions and linkedin/profile-comments cap at postedLimit windows of 24h, week, or month (or any for everything currently visible on their activity feed) — there's no paginated "give me their last two years of comments" mode. For ongoing tracking, that means running the pull on a schedule and storing results yourself, not requesting a longer window in one call.

Which endpoint should you use for which job?

FAQ