# LinkedIn Post Comments Mass scraper (`scrapeai/linkedin-post-comments`) Actor Extract LinkedIn post comments, scrape comments or replies to comments as well as comment social activities such as likes and reactions without compromising security or violating platform policies. - **URL**: https://apify.com/scrapeai/linkedin-post-comments.md - **Developed by:** [ScrapeAI](https://apify.com/scrapeai) (community) - **Categories:** Social media, Automation, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $2.99 / 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 web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ## LinkedIn Post Comments Mass scraper Our powerful tool helps you extract LinkedIn post comments, scrape comments or replies to comments as well as comment social activities such as likes and reactions without compromising security or violating platform policies. It is very helpful for engagement analysis and outreach purposes. ### Key Benefits - **No cookies or account required**: Access comments data without sharing cookies or risking account restrictions - **Low pricing**: $2 per 1k comments. - **Fast response times**: Deliver data in seconds 🚀 - **No caching**: Fresh real-time data on demand. --- ### How It Works #### (Required) List of Post URLs or post comments URL to scrape (`posts`): - When a **post URL** is provided, the actor will scrape all comments under the post. It will also collect up to 5 replies to comments nested inside comments. Note that the total count of results will count root comments and replies according to your input configuration. - When a **post comment URL** is provided, the actor will scrape only that specific comment with nested replies. If you enable `scrapeReplies`, replies will be counted as separate results. #### Other Parameters (Optional): - `maxItems`: Maximum number of comments to scrape per each post. If set to 0, it will scrape all available pages per post. - `postedLimit`: Limit comments to those posted within a certain timeframe. Supported values: `any`, `24h`, `week`, `month`, `3months`, `6months`, `year`. Default is `any`. - `scrapeReplies`: Whether to scrape replies to comments. - `profileScraperMode`: Set this to `short` for basic author info or `main` to enrich comment actors with main profile data (position, profile picture, etc.). --- ### Data You'll Receive - **Comment URL** (`linkedinUrl`) - **Comment text** (`commentary`) - **Number of replies, likes, shares, impressions** (`numComments`, `numShares`, `numImpressions`) - **Reaction type counts** (`reactionTypeCounts`: like, love, insightful, etc.) - **Actor's name** (`actor.name`) - **Actor's LinkedIn URL** (`actor.linkedinUrl`) - **Actor's position** (`actor.position`) - **Actor's profile picture URL** (`actor.pictureUrl`) - **Comment creation date** (`createdAt` and `createdAtTimestamp`) - **Post ID** (`postId`) --- ### ⬇️ Input Parameters | Parameter | Type | Required | Description | | --- | --- | --- | --- | | `posts` | array | Required | List of LinkedIn post URLs or post comment URLs to scrape | | `maxItems` | integer | Optional | Maximum number of comments to scrape per post (default: 10, 0 = all) | | `postedLimit` | string | Optional | Timeframe filter: `any`, `24h`, `week`, `month`, `3months`, `6months`, `year` | | `scrapeReplies` | boolean | Optional | Whether to scrape replies to comments | | `profileScraperMode` | string | Optional | `short` (basic profile info) or `main` (enriched detailed profile info) | #### Example Input JSON ```json { "posts": [ "https://www.linkedin.com/posts/microsoft-events_microsoft-build-has-arrived-in-seattle-and-ugcPost-7329991434395160578-GnK7?utm_source=share&utm_medium=member_desktop&rcm=ACoAACzazy4B3ajZsA0WxWr6m4S77iItYbYCLZM", "https://www.linkedin.com/feed/update/urn:li:activity:7320867199693246465/", "https://www.linkedin.com/feed/update/urn:li:ugcPost:7396563121059872768?commentUrn=urn%3Ali%3Acomment%3A%28ugcPost%3A7396563121059872768%2C7396565439390076928%29&dashCommentUrn=urn%3Ali%3Afsd_comment%3A%287396565439390076928%2Curn%3Ali%3AugcPost%3A7396563121059872768%29" ], "maxItems": 10, "profileScraperMode": "short" } ```` *** ### ⬆️ Sample Output Data ```json { "type": "comment", "id": "7331190065471078400", "linkedinUrl": "https://www.linkedin.com/feed/update/urn:li:activity:7328838056403173380?commentUrn=urn%3Ali%3Acomment%3A%28activity%3A7328838056403173380%2C7331190065471078400%29&dashCommentUrn=urn%3Ali%3Afsd_comment%3A%287331190065471078400%2Curn%3Ali%3Aactivity%3A7328838056403173380%29", "commentary": "❤️", "createdAt": "2025-05-22T05:31:58.534Z", "numComments": 0, "numShares": null, "numImpressions": null, "reactionTypeCounts": [ { "type": "LIKE", "count": 1 } ], "actor": { "id": "ACoAAFsE9LEBl7BKtsoGeoDZz0IvKfmiGgiEtX8", "name": "Leek Gai", "linkedinUrl": "https://www.linkedin.com/in/leek-gai-3a94a6367", "position": "Student at Bugema University", "pictureUrl": "https://media.licdn.com/dms/image/v2/D4D03AQFWtueH_5zHYQ/profile-displayphoto-shrink_800_800/B4DZb4IP4IG0Ac-/0/1747919636435?e=1753315200&v=beta&t=ykKTPu2Mkc6i9uyRaHXm8yziqM3dkd18zLaRQ8dCLdg", "picture": { "url": "https://media.licdn.com/dms/image/v2/D4D03AQFWtueH_5zHYQ/profile-displayphoto-shrink_800_800/B4DZb4IP4IG0Ac-/0/1747919636435?e=1753315200&v=beta&t=ykKTPu2Mkc6i9uyRaHXm8yziqM3dkd18zLaRQ8dCLdg", "width": 800, "height": 800, "expiresAt": 1753315200000 }, "author": false }, "createdAtTimestamp": 1747891918534, "pinned": false, "contributed": false, "edited": false, "postId": "7328838056403173380" } ``` *** ### Linkedin Post Comment API The actor stores results in an Apify dataset. You can export data in various formats such as CSV, JSON, XLS, etc. You can scrape and access data on demand using the API. # Actor input Schema ## `posts` (type: `array`): List of LinkedIn post URLs or post comments URLs to scrape. ## `maxItems` (type: `integer`): Maximum number of comments to scrape per each post. If 0 or empty, scrapes all available comments. ## `postedLimit` (type: `string`): Fetch comments no older than X timeframe. Options: any, 24h, week, month, 3months, 6months, year. ## `scrapeReplies` (type: `boolean`): Whether to scrape replies to comments. ## `profileScraperMode` (type: `string`): Choose mode for scraping profiles of comment authors. 'short' provides basic info, 'main' enriches author profile data. ## `connectionProxy` (type: `object`): Apify proxy configuration. Residential recommended. ## Actor input object example ```json { "posts": [ "https://www.linkedin.com/posts/microsoft-events_microsoft-build-has-arrived-in-seattle-and-ugcPost-7329991434395160578-GnK7?utm_source=share&utm_medium=member_desktop&rcm=ACoAACzazy4B3ajZsA0WxWr6m4S77iItYbYCLZM", "https://www.linkedin.com/feed/update/urn:li:activity:7320867199693246465/", "https://www.linkedin.com/feed/update/urn:li:ugcPost:7396563121059872768?commentUrn=urn%3Ali%3Acomment%3A%28ugcPost%3A7396563121059872768%2C7396565439390076928%29&dashCommentUrn=urn%3Ali%3Afsd_comment%3A%287396565439390076928%2Curn%3Ali%3AugcPost%3A7396563121059872768%29" ], "maxItems": 10, "postedLimit": "any", "scrapeReplies": false, "profileScraperMode": "short", "connectionProxy": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "US" } } ``` # 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 = { "posts": [ "https://www.linkedin.com/posts/microsoft-events_microsoft-build-has-arrived-in-seattle-and-ugcPost-7329991434395160578-GnK7?utm_source=share&utm_medium=member_desktop&rcm=ACoAACzazy4B3ajZsA0WxWr6m4S77iItYbYCLZM", "https://www.linkedin.com/feed/update/urn:li:activity:7320867199693246465/", "https://www.linkedin.com/feed/update/urn:li:ugcPost:7396563121059872768?commentUrn=urn%3Ali%3Acomment%3A%28ugcPost%3A7396563121059872768%2C7396565439390076928%29&dashCommentUrn=urn%3Ali%3Afsd_comment%3A%287396565439390076928%2Curn%3Ali%3AugcPost%3A7396563121059872768%29" ], "maxItems": 10, "postedLimit": "any", "profileScraperMode": "short" }; // Run the Actor and wait for it to finish const run = await client.actor("scrapeai/linkedin-post-comments").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 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); }); // 📚 Want to learn more 📖? Go to → 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 = { "posts": [ "https://www.linkedin.com/posts/microsoft-events_microsoft-build-has-arrived-in-seattle-and-ugcPost-7329991434395160578-GnK7?utm_source=share&utm_medium=member_desktop&rcm=ACoAACzazy4B3ajZsA0WxWr6m4S77iItYbYCLZM", "https://www.linkedin.com/feed/update/urn:li:activity:7320867199693246465/", "https://www.linkedin.com/feed/update/urn:li:ugcPost:7396563121059872768?commentUrn=urn%3Ali%3Acomment%3A%28ugcPost%3A7396563121059872768%2C7396565439390076928%29&dashCommentUrn=urn%3Ali%3Afsd_comment%3A%287396565439390076928%2Curn%3Ali%3AugcPost%3A7396563121059872768%29", ], "maxItems": 10, "postedLimit": "any", "profileScraperMode": "short", } # Run the Actor and wait for it to finish run = client.actor("scrapeai/linkedin-post-comments").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "posts": [ "https://www.linkedin.com/posts/microsoft-events_microsoft-build-has-arrived-in-seattle-and-ugcPost-7329991434395160578-GnK7?utm_source=share&utm_medium=member_desktop&rcm=ACoAACzazy4B3ajZsA0WxWr6m4S77iItYbYCLZM", "https://www.linkedin.com/feed/update/urn:li:activity:7320867199693246465/", "https://www.linkedin.com/feed/update/urn:li:ugcPost:7396563121059872768?commentUrn=urn%3Ali%3Acomment%3A%28ugcPost%3A7396563121059872768%2C7396565439390076928%29&dashCommentUrn=urn%3Ali%3Afsd_comment%3A%287396565439390076928%2Curn%3Ali%3AugcPost%3A7396563121059872768%29" ], "maxItems": 10, "postedLimit": "any", "profileScraperMode": "short" }' | apify call scrapeai/linkedin-post-comments --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapeai/linkedin-post-comments", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Post Comments Mass scraper", "description": "Extract LinkedIn post comments, scrape comments or replies to comments as well as comment social activities such as likes and reactions without compromising security or violating platform policies.", "version": "1.0", "x-build-id": "S3vEBGguFyBLqP4zf" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapeai~linkedin-post-comments/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapeai-linkedin-post-comments", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrapeai~linkedin-post-comments/runs": { "post": { "operationId": "runs-sync-scrapeai-linkedin-post-comments", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrapeai~linkedin-post-comments/run-sync": { "post": { "operationId": "run-sync-scrapeai-linkedin-post-comments", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "posts" ], "properties": { "posts": { "title": "Post URLs / Post Comment URLs", "type": "array", "description": "List of LinkedIn post URLs or post comments URLs to scrape.", "default": [ "https://www.linkedin.com/posts/microsoft-events_microsoft-build-has-arrived-in-seattle-and-ugcPost-7329991434395160578-GnK7?utm_source=share&utm_medium=member_desktop&rcm=ACoAACzazy4B3ajZsA0WxWr6m4S77iItYbYCLZM", "https://www.linkedin.com/feed/update/urn:li:activity:7320867199693246465/", "https://www.linkedin.com/feed/update/urn:li:ugcPost:7396563121059872768?commentUrn=urn%3Ali%3Acomment%3A%28ugcPost%3A7396563121059872768%2C7396565439390076928%29&dashCommentUrn=urn%3Ali%3Afsd_comment%3A%287396565439390076928%2Curn%3Ali%3AugcPost%3A7396563121059872768%29" ], "items": { "type": "string" } }, "maxItems": { "title": "Max Items Per Post", "type": "integer", "description": "Maximum number of comments to scrape per each post. If 0 or empty, scrapes all available comments.", "default": 10 }, "postedLimit": { "title": "Posted Limit (filter)", "enum": [ "any", "24h", "week", "month", "3months", "6months", "year" ], "type": "string", "description": "Fetch comments no older than X timeframe. Options: any, 24h, week, month, 3months, 6months, year.", "default": "any" }, "scrapeReplies": { "title": "Scrape Replies", "type": "boolean", "description": "Whether to scrape replies to comments.", "default": false }, "profileScraperMode": { "title": "Profile Scraper Mode", "enum": [ "short", "main" ], "type": "string", "description": "Choose mode for scraping profiles of comment authors. 'short' provides basic info, 'main' enriches author profile data.", "default": "short" }, "connectionProxy": { "title": "Proxy Configuration", "type": "object", "description": "Apify proxy configuration. Residential recommended.", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "US" } } } }, "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 } } } } } } } } } } ```