# LinkedIn Post Comments & Engagements Scraper (`api-empire/post-comments-engagements-scraper-linkedin`) Actor πŸ’¬ LinkedIn Post Comments & Engagements Scraper gathers commenters, comment text, replies, reaction types & counts, timestamps, and profiles from public postsβ€”no cookies needed. ⚑ Perfect for social listening, content strategy, competitor analysis & analytics. πŸ“Š Fast, clean exports. - **URL**: https://apify.com/api-empire/post-comments-engagements-scraper-linkedin.md - **Developed by:** [API Empire](https://apify.com/api-empire) (community) - **Categories:** Social media, Developer tools, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $4.99 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Post Comments & Engagements Scraper for LinkedIn | No Cookies Scrape LinkedIn post comments, replies, reactions, and author info in batch (up to 500 posts per run). No browser cookies required by default; optional `li_at` cookie for authenticated access. ### Why use this actor? - **Bulk scraping**: Add multiple post URLs or numeric activity IDs in one run. - **Structured output**: Each comment includes text, author (name, headline, profile URL, picture), posted_at (timestamp, date, relative), stats (reactions, reply count), and nested replies. - **Proxy fallback**: Runs without proxy by default; if LinkedIn blocks, automatically falls back to datacenter then residential proxy (with retries). ### Input | Field | Type | Required | Description | |-------|------|----------|-------------| | **Post URLs or IDs** | array (URLs) | Yes | LinkedIn post URLs or activity IDs (e.g. `7289521182721093633` or full post URL). | | **Proxy Configuration** | object | No | Apify proxy. Leave default for no proxy; actor will fallback on block. | | **Page Number** | integer | No | Pagination (default: 1). | | **Sort order** | string | No | `REVERSE_CHRONOLOGICAL` (most recent) or `RELEVANCE`. | | **Result limit per post** | integer | No | Max comments per post (1–500, default 100). In *Advanced options*. | | **LinkedIn session cookie (li_at)** | string (secret) | No | Optional. Your `li_at` cookie for logged-in scraping. In *Advanced options*. | #### Example input (JSON) ```json { "startUrls": [ { "url": "https://www.linkedin.com/feed/update/urn:li:activity:7289521182721093633/" }, { "url": "7289521182721093633" } ], "sortOrder": "REVERSE_CHRONOLOGICAL", "resultLimitPerPost": 100 } ```` ### Output Dataset items: one per post. - **postUrl**: The post URL used. - **comments**: Array of comment objects. Each has: - `comment_id`, `text`, `posted_at` (timestamp, date, relative) - `author` (name, headline, profile\_url, profile\_picture) - `stats` (total\_reactions, reactions by type, comments count) - `replies` (same structure), `comment_url`, `is_pinned`, `is_edited`, `post_input`, `totalComments` ### How to use (Apify Console) 1. Open [Apify Console](https://console.apify.com) β†’ **Actors**. 2. Find **Post Comments & Engagements Scraper for LinkedIn** and open it. 3. Under **Input**, add post URLs or IDs (use **+ Add** or **Bulk edit**). 4. Optionally set proxy, sort order, and **Advanced options** (result limit, `li_at`). 5. Click **Start**. Watch the **Log** tab; results appear in the **Output** dataset as each post is done. ### Cautions - Data is from **publicly available** sources only. No private or password-protected content. - You are responsible for compliance with LinkedIn’s terms, privacy laws, and anti-spam regulations. ### What are other Linkedin scraping tools? If you want to scrape specific Linkedin data, you can use any of the dedicated scrapers below for faster and more targeted results. | Scraper Name | Scraper Name | |---|---| | [LinkedIn Ads Scraper](https://apify.com/api-empire/linkedin-ads-scraper) | [Linkedin Open Profile Status](https://apify.com/api-empire/linkedin-open-profile-status) | | [Linkedin B2b Email Scraper](https://apify.com/api-empire/linkedin-b2b-email-scraper) | [Linkedin Phone Number Scraper](https://apify.com/api-empire/linkedin-phone-number-scraper) | | [Linkedin B2b Lead Scraper](https://apify.com/api-empire/linkedin-b2b-lead-scraper) | [LinkedIn Post Comments Scraper](https://apify.com/api-empire/linkedin-post-comments-scraper) | | [Linkedin B2b Phone Number Scraper](https://apify.com/api-empire/linkedin-b2b-phone-number-scraper) | [Linkedin Post Reactions Scraper](https://apify.com/api-empire/linkedin-post-reactions-scraper) | | [Linkedin Company About Scraper](https://apify.com/api-empire/linkedin-company-about-scraper) | [LinkedIn Post Scraper](https://apify.com/api-empire/linkedin-post-scraper) | | [Linkedin Company Employees](https://apify.com/api-empire/linkedin-company-employees) | [LinkedIn Posts URL (Profile)](https://apify.com/api-empire/linkedin-posts-url-profile) | | [Linkedin Company Employees Scraper](https://apify.com/api-empire/linkedin-company-employees-scraper) | [Linkedin Profile And Company Posts Scraper](https://apify.com/api-empire/linkedin-profile-and-company-posts-scraper) | | [Linkedin Company Post Scraper](https://apify.com/api-empire/linkedin-company-post-scraper) | [Linkedin Profile Email Scraper](https://apify.com/api-empire/linkedin-profile-email-scraper) | | [Linkedin Company Profile Scraper](https://apify.com/api-empire/linkedin-company-profile-scraper) | [Linkedin Profile Lead Scraper](https://apify.com/api-empire/linkedin-profile-lead-scraper) | | [LinkedIn Company Scraper](https://apify.com/api-empire/linkedin-company-scraper-actor) | [Linkedin Profile Phone Number Scraper](https://apify.com/api-empire/linkedin-profile-phone-number-scraper) | | [Linkedin Email Scraper](https://apify.com/api-empire/linkedin-email-scraper) | [Linkedin Profile Post Scraper](https://apify.com/api-empire/linkedin-profile-post-scraper) | | [Linkedin Jobs Scraper](https://apify.com/api-empire/linkedin-jobs-scraper) | [LinkedIn Profile Scraper](https://apify.com/api-empire/linkedin-profile-scraper) | | [Linkedin Lead Scraper](https://apify.com/api-empire/linkedin-lead-scraper) | [LinkedIn Search Jobs Scraper](https://apify.com/api-empire/linkedin-search-jobs-scraper) | # Actor input Schema ## `startUrls` (type: `array`): πŸ“Ž Enter one or more LinkedIn post URLs or numeric activity IDs. You can paste full URLs (e.g. https://www.linkedin.com/feed/update/urn:li:activity:123456789/) or just the activity ID (e.g. 123456789). Add multiple entries for bulk scraping β€” the actor processes each post and saves comments to the dataset. One URL or ID per line. πŸš€ ## `liAt` (type: `string`): πŸ” Optional. If you want to scrape as a logged-in user, paste your li\_at cookie from LinkedIn (get it from your browser dev tools while logged in). Leave this empty to run without login β€” the actor will still attempt to fetch public comment data. Using a cookie can help with rate limits or access on some posts. ## `pageNumber` (type: `integer`): πŸ“ƒ The page number for comment pagination (1-based). Use this if you want to start from a specific page of results. Default is 1 (first page). ## `sortOrder` (type: `string`): πŸ“Š Choose how comments are sorted for each post. Most recent (default) returns newest comments first (REVERSE\_CHRONOLOGICAL). Most relevant returns LinkedIn’s relevance order (RELEVANCE). ## `resultLimitPerPost` (type: `integer`): πŸ“ˆ Maximum number of comments to fetch per post (1–500). Default is 100. Increase this to get more comments per post; lower it for faster runs or when you only need a sample. ## `proxyConfiguration` (type: `object`): πŸ”’ Optional. By default the actor sends requests directly to LinkedIn (no proxy). If LinkedIn blocks or rate-limits, the actor automatically falls back to Apify datacenter proxy, then to residential proxy with up to 3 retries, and sticks with residential for the rest of the run. You can also configure a proxy here to use from the start (e.g. Apify proxy with a specific group). All proxy changes are logged in the run log. πŸ›‘οΈ ## Actor input object example ```json { "startUrls": [ "https://www.linkedin.com/feed/update/urn:li:activity:7289521182721093633/", "7289521182721093633" ], "pageNumber": 1, "sortOrder": "REVERSE_CHRONOLOGICAL", "resultLimitPerPost": 100 } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "startUrls": [ "https://www.linkedin.com/feed/update/urn:li:activity:7289521182721093633/", "7289521182721093633" ] }; // Run the Actor and wait for it to finish const run = await client.actor("api-empire/post-comments-engagements-scraper-linkedin").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "startUrls": [ "https://www.linkedin.com/feed/update/urn:li:activity:7289521182721093633/", "7289521182721093633", ] } # Run the Actor and wait for it to finish run = client.actor("api-empire/post-comments-engagements-scraper-linkedin").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "startUrls": [ "https://www.linkedin.com/feed/update/urn:li:activity:7289521182721093633/", "7289521182721093633" ] }' | apify call api-empire/post-comments-engagements-scraper-linkedin --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=api-empire/post-comments-engagements-scraper-linkedin", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Post Comments & Engagements Scraper", "description": "πŸ’¬ LinkedIn Post Comments & Engagements Scraper gathers commenters, comment text, replies, reaction types & counts, timestamps, and profiles from public postsβ€”no cookies needed. ⚑ Perfect for social listening, content strategy, competitor analysis & analytics. πŸ“Š Fast, clean exports.", "version": "0.1", "x-build-id": "iWLrQk8HflZcxteWD" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/api-empire~post-comments-engagements-scraper-linkedin/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-api-empire-post-comments-engagements-scraper-linkedin", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/api-empire~post-comments-engagements-scraper-linkedin/runs": { "post": { "operationId": "runs-sync-api-empire-post-comments-engagements-scraper-linkedin", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/api-empire~post-comments-engagements-scraper-linkedin/run-sync": { "post": { "operationId": "run-sync-api-empire-post-comments-engagements-scraper-linkedin", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "startUrls" ], "properties": { "startUrls": { "title": "πŸ”— Post URLs or IDs (required)", "type": "array", "description": "πŸ“Ž Enter one or more LinkedIn post URLs or numeric activity IDs. You can paste full URLs (e.g. https://www.linkedin.com/feed/update/urn:li:activity:123456789/) or just the activity ID (e.g. 123456789). Add multiple entries for bulk scraping β€” the actor processes each post and saves comments to the dataset. One URL or ID per line. πŸš€", "items": { "type": "string" } }, "liAt": { "title": "πŸͺ LinkedIn session cookie (li_at)", "type": "string", "description": "πŸ” Optional. If you want to scrape as a logged-in user, paste your li_at cookie from LinkedIn (get it from your browser dev tools while logged in). Leave this empty to run without login β€” the actor will still attempt to fetch public comment data. Using a cookie can help with rate limits or access on some posts." }, "pageNumber": { "title": "πŸ“„ Page Number", "minimum": 1, "type": "integer", "description": "πŸ“ƒ The page number for comment pagination (1-based). Use this if you want to start from a specific page of results. Default is 1 (first page).", "default": 1 }, "sortOrder": { "title": "πŸ”€ Sort order", "enum": [ "REVERSE_CHRONOLOGICAL", "RELEVANCE" ], "type": "string", "description": "πŸ“Š Choose how comments are sorted for each post. Most recent (default) returns newest comments first (REVERSE_CHRONOLOGICAL). Most relevant returns LinkedIn’s relevance order (RELEVANCE).", "default": "REVERSE_CHRONOLOGICAL" }, "resultLimitPerPost": { "title": "🎯 Result limit per post", "minimum": 1, "maximum": 500, "type": "integer", "description": "πŸ“ˆ Maximum number of comments to fetch per post (1–500). Default is 100. Increase this to get more comments per post; lower it for faster runs or when you only need a sample.", "default": 100 }, "proxyConfiguration": { "title": "🌐 Proxy Configuration", "type": "object", "description": "πŸ”’ Optional. By default the actor sends requests directly to LinkedIn (no proxy). If LinkedIn blocks or rate-limits, the actor automatically falls back to Apify datacenter proxy, then to residential proxy with up to 3 retries, and sticks with residential for the rest of the run. You can also configure a proxy here to use from the start (e.g. Apify proxy with a specific group). All proxy changes are logged in the run log. πŸ›‘οΈ" } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```