LinkedIn Post Comments

Extract root comments and available top replies from public LinkedIn post URLs, including commenter names, profile URLs, headlines, timestamps, reply totals, and reaction breakdowns. Batch up to 1,000 posts and export structured JSON, CSV, or Excel—no LinkedIn cookies or login required.

Try it on Apify See example code

users, last 30 days: 1
runs, last 30 days: 28
runs, all time: 73
users, all time: 3

Live figures from Apify's public API, refreshed every hour.

LinkedIn Post Comments specifications

Platform	LinkedIn
Apify actor	`data-slayer/linkedin-post-comments`
Price	from $1.50 per 1,000 results
Inputs	`post_urlsmax_comments_per_post`
Output	26 documented fields per row
Export formats	JSON, CSV, Excel, XML, HTML
LinkedIn login or cookies	Not required
Integrations	Apify REST API, JavaScript and Python clients, n8n, Make, Zapier
Last updated	September 25, 2026 (version 1.0.5)

Run it from code

Replace the example input with your own. You need an Apify API token, which you can create in your Apify account settings.

POST /v2/acts/data-slayer~linkedin-post-comments/run-sync-get-dataset-items

request

curl -X POST "https://api.apify.com/v2/acts/data-slayer~linkedin-post-comments/run-sync-get-dataset-items" \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "post_urls": [
      "https://www.linkedin.com/feed/update/urn:li:activity:7408723748973056001"
    ],
    "max_comments_per_post": 100
  }'

each result row26 fields

{
  "post_url": string,
  "post_id": string | null,
  "post_comment_count": integer | null,
  "comment_id": string | null,
  "comment_url": string | null,
  "comment_text": string | null,
  "commented_at": string | null,
  "commented_at_timestamp": integer | null,
  "is_pinned": boolean,
  "is_edited": boolean,
  "reply_count": integer,
  "top_reply_count": integer,
  "total_reaction_count": integer,
  "like_count": integer,
  // + 12 more fields
}

Input parameters

2 parameters you can set for each run.

parameter	type	description
`post_urls`required	array	LinkedIn Post URLs Required. Add 1–1,000 public LinkedIn post URLs. Supported formats include linkedin.com/posts/…-activity-…, linkedin.com/posts/…-ugcPost-…, and linkedin.com/feed/update/urn:li:activity:…. Tracking parameters are removed. Comment-specific URLs are normalized to their parent post; targeted single-comment scraping is not supported.
`max_comments_per_post`	integer	Maximum comments per post Maximum number of root comments to save for each post. Reply data returned with those comments does not count toward this limit. Enter 0 to fetch all available comments, with a 100-page safety cap per post.

Output fields

Each result is one row with these 26 fields, taken from the scraper's dataset schema.

field	type	description
`post_url`	string	Canonical LinkedIn post URL supplied in the input.
`post_id`	string \| null	Numeric LinkedIn activity identifier kept as a string for precision safety.
`post_comment_count`	integer \| null	Total root-comment count reported by the source when available.
`comment_id`	string \| null	Numeric LinkedIn comment identifier kept as a string for precision safety.
`comment_url`	string \| null	Comment URL
`comment_text`	string \| null	Comment text
`commented_at`	string \| null	ISO 8601 UTC timestamp derived from commented_at_timestamp.
`commented_at_timestamp`	integer \| null	Unix timestamp in milliseconds.
`is_pinned`	boolean	Pinned
`is_edited`	boolean	Edited
`reply_count`	integer	Total replies reported for the root comment.
`top_reply_count`	integer	Number of reply objects included in top_replies; this can be lower than reply_count.
`total_reaction_count`	integer	Total reactions
`like_count`	integer	Likes
`praise_count`	integer	Praise reactions
`empathy_count`	integer	Empathy reactions
`appreciation_count`	integer	Appreciation reactions
`interest_count`	integer	Interest reactions
`other_reaction_count`	integer	Any non-negative reaction counters not represented by the five named fields.
`commenter_id`	string \| null	Stable LinkedIn member or entity ID when supplied by the source.
`commenter_type`	string	Commenter type
`commenter_name`	string \| null	Commenter name
`commenter_headline`	string \| null	Commenter headline
`commenter_linkedin_url`	string \| null	Commenter LinkedIn URL
`commenter_image_url`	string \| null	Commenter image URL
`top_replies`	array	Top reply details returned with this root comment. These do not count toward max_comments_per_post.

Pricing

Pay-per-event pricing, billed through your Apify account. Where plan tiers are listed, paid Apify plans get a lower price per event.

event	price	per 1,000, by Apify plan
Post comment result One unique root LinkedIn post comment written to the default dataset. Available top replies nested in that record are included.	$0.002 each	Free $2.00 Bronze $2.00 Silver $2.00 Gold $1.50 Platinum $1.50 Diamond $1.50

Questions

How much does LinkedIn Post Comments cost?

LinkedIn Post Comments uses pay-per-event pricing on Apify. The main charge is $0.002 per post comment result, which is $2.00 per 1,000. On higher Apify plans the price drops to $1.50 per 1,000.

Do I need to log in to LinkedIn or share cookies?

No. LinkedIn Post Comments works without your LinkedIn login or cookies. You only need an Apify account to run it.

Can I use LinkedIn Post Comments through an API?

Yes. Send a POST request to the Apify API with your input and read the results as JSON, or use Apify's official clients for JavaScript and Python. The code examples on this page are ready to copy.

What data does LinkedIn Post Comments return?

Each result is a structured row. Its dataset schema lists 26 fields, including post_url, post_id, post_comment_count, comment_id, and comment_url.

What formats can I export?

Results are stored in an Apify dataset. You can read it through the API as JSON, or download it as CSV, Excel, XML or HTML.

LinkedIn Post Comments

LinkedIn Post Comments specifications

Run it from code

Input parameters

Output fields

Pricing

Questions

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