Say a founder posts a contrarian take on B2B hiring and it takes off: 300 likes, 40 comments. The 300 likers are a name dump. The 40 commenters did something else: they argued, agreed hard, or asked a follow-up question. Forty people just told you what they think about your exact topic, in their own words, under their own name. That second list is the one worth exporting, and it is usually the shorter one, which makes the whole job faster.
Most guides treat likers and commenters as the same job with a different button. They are not, and this guide is about the difference. It is built around the question the roundups skip: how much access to your own account does each method require, and who holds that access when you are done.
Why a commenter outranks a liker
Start here, because it changes what you should even bother exporting.
A like is a reflex. It costs nothing, it is often "I read the first line", and on a viral post half the reactions come from people who will never buy anything from anyone. A comment costs visible effort and a small amount of social risk, and it usually contains an actual opinion. That opinion is both a stronger intent signal and a ready-made opening line.
The practical takeaway: on a post with 300 likes and 40 comments, the 40 comments are the better prospecting list, not because 40 is more manageable than 300 (though it is), but because each of those 40 people told you something you can respond to. For the full argument on reading engagement as buying intent, see signal-based selling on LinkedIn.
The six methods, ranked by what they cost your account
There are six real ways to get the commenter list off a post. They differ on speed and price, but the axis that actually matters is account exposure.
Two rows get misread constantly, so they are worth expanding.
The cloud tool row is the highest risk and the most heavily marketed. You paste your session token into a dashboard, and from that point the tool replays your logged-in session from its own infrastructure. Your account is now active from an IP that is not yours, on a schedule you did not set. That mismatch between where your account normally signs in and where it is suddenly running a comment scraper is one of the most legible automation signals there is. The export works. The exposure is real, and it lasts until you rotate the session.
The official API row is a genuine dead end. LinkedIn's partner APIs do not expose the comment thread of an arbitrary post to third-party developers. If a page tells you to "just use the official API" to pull commenters, it has not tried. This matters because it removes the one method people assume is the safe, sanctioned option. It does not exist for this.
The manual method, and where it stops
Open the post, scroll the comments, read them. This is free, it breaks no rules, and for a post with a dozen comments it is honestly the right answer. You can even reply in-thread, which is warmer than a cold DM anyway.
It stops scaling fast. LinkedIn loads comments in batches and buries replies under "show more replies", there is no export, and there is no filter. Past fifty or so comments you are scrolling, clicking "load more", and retyping names and headlines into a spreadsheet, where every hand-copied row is a fresh chance to mistype a name or grab the wrong headline. This is fine as a one-off. It is not a workflow.
Getting the list without connecting anything
Comments on a public post are public. A server can read them the same way a person reading the thread can, without acting as your account and without ever touching your session.
- Copy the post permalink. Open the post on its own page (click the timestamp) and copy the full URL from the address bar, not the shortened share link.
- Paste it into the finder. The free LinkedIn comments finder takes the URL and returns the people who commented. Nothing is connected, so nothing is exposed. It needs no account and no extension.
- Filter before you export, not after. This is the step everyone skips. Cutting the list down while it is still on screen is faster than cleaning a CSV later, and it forces you to actually look at who these people are.
Time: a couple of minutes. Account risk: none, because nothing is connected.
If you also want the reactions from the same post, the free LinkedIn likes finder works identically, and the full likers guide walks through that side. For a side-by-side of the dedicated comment export tools, see LinkedIn comment export tools compared.
The reason this method exists is a specific architectural choice. Reading a public comment thread and operating your LinkedIn account are two different actions, and most tools fuse them, which is why exporting commenters usually costs you a session token. Split them and the export never touches your account: you pull the 40 commenters, check fit, and draft replies to what they actually wrote, all with nothing connected. A cookie only enters at the moment you send. We call that "cookieless until outreach", and it matters more on a commenter list than a liker list, because the whole payoff, answering a specific comment, happens well before any account action is needed.
The step that decides whether this was worth doing
A list of 40 commenters is not 40 leads, and the export is the easy half. Two filters do most of the work of turning it into a prospect list:
- Fit. Does this person match who you actually sell to? A headline is a weak proxy. Company shape, seniority, and whether they can buy usually matter more than the job title string.
- Relevance of the post. Someone who commented on a post about the exact problem you solve is worth far more than someone who commented on a viral post about hiring or motivation. The topic is part of the signal, not just the act of commenting.
Skipping qualification is why most engagement exports die in a spreadsheet. The payoff for doing it shows up in reply rates. Belkins' LinkedIn outreach study, drawing on more than 15 million touchpoints, found campaigns to people you are already connected to replying at 12.2%, against 7.9% for cold connection-request campaigns. That gap is real, but it evaporates if "warm" only means "this person clicked something once". A qualified commenter who left their own words on your topic is about as warm as a cold list gets, which is the whole reason to prefer the shorter comment list.
What to do with the qualified list
The specific comment is your whole advantage, and it is easy to waste. "I saw you commented on a post about X" is not personalisation, it is surveillance with extra steps. The better version answers what they said: they made a point, you have something useful to add to it, and that is why you are writing. Reference the idea, not the click. The same Belkins study puts a number on it: once a request is accepted, one that carried a short personalised note draws replies at 8.2%, against 5.3% for a blank request, a 55% lift. A commenter's own words are the easiest personalised note you will ever write, so a blank request throws away the one thing the export gave you.
If you are sending from your own account, pace it. The list arriving all at once does not mean the messages should. LinkedIn's own comfortable rate for connection requests is roughly 100 a week, and safe outreach tools sit well under the platform's hard ceilings on visits, invites, and messages per day. Forty new commenters do not become forty invites this afternoon.
Every viral post is 100+ warm conversations waiting.
Tell your agent who you want to reach. It finds leads, qualifies them, sends personalized outreach, and follows up.
Where the compliance line actually sits
Reading a public comment thread is not the same as automating your account, and the two get conflated constantly. The short version: public data is public, and the enforcement action of the last several years has landed on bulk resale of profile data and on tools that operate accounts at machine speed, not on reading a page that anyone can read.
The account risk in the table above is a detection-and-restriction risk, not a legality question, and it comes entirely from the methods that act as you. The longer version, including what the Proxycurl shutdown and the hiQ litigation actually established, is in the LinkedIn data compliance guide.
Can you export LinkedIn post commenters without an account?
Yes, for public posts. The comment thread on a public post is publicly readable, so a tool can retrieve the commenters without you connecting or signing in. Posts shared to a restricted audience are not publicly readable and will not show up. No extension and no login are required.
Are commenters or likers the better lead source?
Commenters, in almost every case. Commenting costs visible effort and usually contains an opinion, which gives you both a stronger intent signal and a ready-made opening line. Liker lists are longer, noisier, and give you nothing but a name to work with.
Does exporting post commenters get your account restricted?
Reading a public post from a server never touches your account, so there is nothing to restrict. The restriction risk comes from methods that act as you: browser extensions and cloud tools that replay your session from their own servers. Those operate your account, which is what detection looks for.
Is there an official LinkedIn API for post comments?
No. LinkedIn's partner APIs do not expose the comment thread of an arbitrary post to outside developers. Any guide telling you to use the official API to pull commenters is describing something that is not available, so treat that advice as a sign the page has not tested it.
How many commenters can you export from one post?
The limit is the post, not the method. Most posts have far fewer real comments than people expect once you strip out replies and reactions to comments, and the useful subset after qualifying for fit is smaller still. Optimising for raw list size is usually the wrong goal.
