# Linkedin Profile Posts Scraper (`scraperoka/linkedin-profile-posts-scraper`) Actor 🔎 LinkedIn Profile Posts Scraper extracts post content, engagement metrics, and author details from public LinkedIn profiles. 📈 Perfect for B2B research, lead gen, sentiment tracking & competitive insights—save time and scale your outreach. - **URL**: https://apify.com/scraperoka/linkedin-profile-posts-scraper.md - **Developed by:** [Scraperoka](https://apify.com/scraperoka) (community) - **Categories:** Social media, Lead generation, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.01 / 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 ### Linkedin Profile Posts Scraper 🎯 Manually visiting profiles to collect post content wastes hours and quickly becomes impossible to scale. **Linkedin Profile Posts Scraper** automatically extracts LinkedIn profile post data (including author info, post text, timestamps, and engagement stats) so you can build datasets fast with a LinkedIn post scraper and LinkedIn profile posts downloader workflow. It’s ideal for marketers, recruiters, and growth teams who need LinkedIn posts data extractor results at speed—often enough for thousands of records in minutes. --- ### What You Get: Sample Output Here's a sample record from a single run: ```json { "urn": { "activity_urn": "1234567890123456789", "share_urn": "2345678901234567890", "ugcPost_urn": null }, "full_urn": "urn:li:activity:1234567890123456789", "posted_at": { "date": "2026-05-22 14:36:10", "relative": "2d", "timestamp": 1768526170000 }, "text": "Excited to share our latest update...\n\n#growth #linkedin", "url": "https://www.linkedin.com/feed/update/urn:li:activity:1234567890123456789", "post_type": "regular", "author": { "first_name": "Alex", "last_name": "Johnson", "headline": "Marketing leader | building growth systems", "username": "alex-johnson", "profile_url": "https://www.linkedin.com/in/alex-johnson", "profile_picture": "https://example.com/profile-picture.jpg" }, "stats": { "total_reactions": 128, "like": 128, "support": 0, "love": 0, "insight": 0, "celebrate": 0, "funny": 0, "comments": 9, "reposts": 0 }, "media": { "type": "image", "url": "https://example.com/post-image.jpg", "images": [ { "url": "https://example.com/post-image.jpg", "width": 1080, "height": 1350 } ] } } ```` | Field | Type | What It Tells You | |---|---|---| | `urn` | object | Keeps internal LinkedIn activity identifiers for traceability and de-duplication logic | | `urn.activity_urn` | string | null | The post’s activity identifier tied to the original feed item | | `urn.share_urn` | string | null | A share identifier when available (useful for shared content analysis) | | `urn.ugcPost_urn` | string | null | A UGC post identifier when available | | `full_urn` | string | null | Canonical activity URN (useful as a stable key) | | `posted_at` | object | Absolute and relative timing for the post | | `posted_at.date` | string | null | A formatted datetime string when the post timestamp is available | | `posted_at.relative` | string | null | Human-friendly “time ago” text as seen on the post page | | `posted_at.timestamp` | number | null | Raw timestamp value (milliseconds) for analytics | | `text` | string | The post’s main commentary text (great for sentiment/keyword analysis) | | `url` | string | Direct URL to the post (handy for verification) | | `post_type` | string | Always returned as `regular` in the actor output | | `author` | object | LinkedIn profile metadata for attribution | | `author.profile_url` | string | Normalized profile URL for the author (in, showcase, or company styles) | | `stats` | object | Engagement metrics (reactions/likes and comments, plus zero-filled categories) | | `media` | object | Post media type (`text`, `image`, or `video`) plus extracted image/video URLs | Export your dataset as JSON, CSV, or Excel — straight from the Apify dashboard. *** ### Why Linkedin Profile Posts Scraper? There are a lot of ways to pull data from LinkedIn — here’s what sets Linkedin Profile Posts Scraper apart. #### Post-ready records, not just links Linkedin Profile Posts Scraper returns structured records with author metadata, post text, timestamps, URLs, and engagement stats—so your LinkedIn post analytics scraper workflow can start immediately. #### Clean, consistent output structure Each post result follows a consistent schema (`author`, `posted_at`, `stats`, `media`), which makes it easier to feed directly into dashboards, tagging pipelines, or downstream ETL. #### Resilient scraping with practical fallbacks The actor includes retries and fallback logic to improve success rates when some requests fail or when pages aren’t accessible in one discovery path. #### Built for bulk extraction with a per-URL limit You control how many posts get scraped per provided URL using `limit`, making it straightforward to run quick tests or build larger exports. *** ### Configuring Your Run Drop this into your `input.json` to get started: ```json { "url": "https://www.linkedin.com/showcase/linkedin-news/", "limit": 20 } ``` | Parameter | Required | What It Does | |---|---:|---| | `url` | ✅ | The LinkedIn profile, showcase, or company URL you want to scrape posts from | | `limit` | ⬜ | Maximum number of posts to scrape per provided `url` (minimum is 1) | *** ### Core Capabilities #### LinkedIn profile posts discovery Linkedin Profile Posts Scraper is designed to discover post URLs from the provided profile/showcase/company page, then process each post to extract structured content. #### Author context included with every post For each post, the actor extracts author fields like `first_name`, `last_name` (when available), `headline`, `username`, `profile_url`, and `profile_picture` so your dataset is ready for attribution and analysis. #### Engagement & timing for quick analytics You get post `text`, `posted_at` (including `date`, `relative`, and `timestamp`), plus `stats` such as `total_reactions` / `like` and `comments`—useful for engagement trend analysis. #### Media extraction for richer content analysis The actor captures media details in a `media` object, including whether the post is `image` or `video`, plus image URLs (with width/height) when available. #### Retry logic for better extraction reliability When a request fails, the actor uses retry logic with delays to improve the chances of successful retrieval, making it more reliable than a basic LinkedIn posts data extractor. In short: Linkedin Profile Posts Scraper produces export-ready LinkedIn profile posts downloader results with consistent structure. *** ### Who Gets the Most Out of This Here's how different teams put Linkedin Profile Posts Scraper to work: **Marketing and growth teams** can collect recent post content from competitor or partner profiles, then analyze messaging themes, timing, and engagement to guide campaign planning. **Recruiters and talent sourcers** can build a post-based view of candidates or employers by scraping public profile posts and attaching clean author context for easier shortlisting and reporting. **Sales and outreach teams** can use Linkedin Profile Posts Scraper as a LinkedIn public posts scraper to turn profile URLs into usable datasets that help inform personalized outreach angles. **Data analysts and researchers** benefit from the structured output (including `posted_at.timestamp`, `stats`, and `media`) for segmentation, KPI tracking, and content performance comparisons across profiles. **Developers and automation specialists** can treat this as a LinkedIn URL to posts scraper that generates consistent JSON records, making it easier to integrate into pipelines with a scheduled run and API-based fetching. *** ### Step-by-Step: How to Use It No coding needed. Here's how to run Linkedin Profile Posts Scraper from start to finish: 1. **Open the actor on Apify** — visit [console.apify.com](https://console.apify.com) and open *Linkedin Profile Posts Scraper*. 2. **Enter your inputs** — add your target `url` and (optionally) set `limit` to control how many posts to extract. 3. **Configure proxy settings (if needed)** — use Apify’s proxy controls for improved reliability on larger batches. 4. **Hit Run** and watch the live log for progress as posts are discovered and processed. 5. **View results in the dataset tab** — every processed post is appended with the structured output. 6. **Export as JSON, CSV, or Excel** — download the dataset in your preferred format from the Apify dashboard. The whole process takes under 5 minutes to set up. *** ### Integrations & Export Options Once your data is collected, Linkedin Profile Posts Scraper plugs directly into your existing workflow. You can export results from the Apify dataset tab in common formats like JSON, CSV, or Excel. If you want to automate downstream steps, you can connect the actor to your stack using Apify’s API capabilities, and use no-code automation options like Zapier/Make for pushing extracted LinkedIn posts data extractor results to tools you already use. You can also schedule runs so your LinkedIn content scraper data stays updated over time—without manual effort. For full details, see the Apify API documentation at https://apify.com/docs/api. *** ### Pricing & Free Trial Linkedin Profile Posts Scraper runs on the Apify platform, which offers a **free tier** — no credit card required to get started. Free tier usage typically provides enough credits for several test runs so you can validate your Linkedin profile post scraper results before scaling. Beyond the free tier, usage is generally pay-as-you-go based on Apify platform compute units (CU), and you only pay for the compute needed to run the actor (rather than a per-row extraction fee). For the most up-to-date plan and billing details, check the Apify pricing page. Start for free at [apify.com](https://apify.com) and scale when you're ready. *** ### Reliability & Performance | What We Handle | How | |---|---| | Rate limiting | The actor is designed to keep requests controlled and practical for scraping jobs | | Retries on failed fetches | Includes retry logic for improved success rates | | Access issues on some pages | Uses fallback discovery paths when a page isn’t accessible | | Output completeness during runs | Extracted posts are processed up to the configured `limit` | | Scale testing | Works well for small tests and repeatable batch runs | **Limitations:** This actor is intended for scraping publicly accessible content. Pages that require login or otherwise block access may not yield results. For enterprise-scale runs, contact us to discuss custom configurations. *** ### Frequently Asked Questions #### Is there a free plan or trial for Linkedin Profile Posts Scraper? Yes. Apify offers a free tier with usage credits so you can run Linkedin Profile Posts Scraper and confirm the output quality before scaling. #### Do I need to log in to LinkedIn to use this? No. The actor is built to scrape posts from publicly accessible pages. If a profile view is login-gated, the actor may not return results for that page. #### How accurate is the data extracted by Linkedin Profile Posts Scraper? The accuracy depends on what’s publicly available on the post and profile pages. The actor extracts the post `text`, `posted_at` timing, and `stats` as presented in the page content it can access. #### How many results can I get per run? You control this with the `limit` input, which sets the maximum number of posts scraped per provided `url` (minimum 1). #### How fresh is the data? The actor fetches content at run time, so records reflect what was available during your specific run. For continuous updates, schedule repeated runs and track changes over time. #### Is this legal? Does it comply with GDPR / CCPA? This tool is for scraping **publicly available data**, and it’s your responsibility to ensure your use complies with GDPR, CCPA, and applicable platform Terms of Service. Always apply appropriate lawful basis, consent, and retention rules for your use case. #### Can I export results to Google Sheets or Excel? Yes. You can export from the Apify dataset tab, including JSON and CSV/Excel-friendly formats. If you’re using Google Sheets directly, you can connect via your preferred automation or import flow. #### Can I run this on a schedule automatically? Yes. You can schedule Apify actor runs to keep your Linkedin profile post scraper dataset updated automatically. #### Can I access this via API? Yes. You can trigger and fetch run outputs programmatically using the Apify API. See https://apify.com/docs/api for details. #### What happens if the actor hits an error? The actor includes retries and fallback discovery logic to improve resilience. If a post fails to fetch or parse, it may be skipped, and the dataset will contain only successfully processed results up to the configured `limit`. *** ### Need Help or Have a Request? Got a question about Linkedin Profile Posts Scraper or want a new feature added? Reach out at . We actively maintain this actor and respond to user feedback. Some ideas we can add include keyword-based filtering and export hooks for automation workflows. *** ### Disclaimer & Responsible Use *Linkedin Profile Posts Scraper is the fastest, most reliable way to build LinkedIn posts datasets from public profiles — start your free run today.* **publicly available data** only. The actor does not access private accounts, login-gated content, or password-protected pages. You’re responsible for GDPR, CCPA, and platform Terms compliance; for data removal requests contact . Use responsibly, ethically, and only for lawful purposes. # Actor input Schema ## `url` (type: `string`): The LinkedIn profile, showcase, or company URL to scrape posts from. ## `limit` (type: `integer`): Maximum number of posts to scrape per provided URL. ## Actor input object example ```json { "url": "https://www.linkedin.com/showcase/linkedin-news/", "limit": 20 } ``` # 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 = { "url": "https://www.linkedin.com/showcase/linkedin-news/" }; // Run the Actor and wait for it to finish const run = await client.actor("scraperoka/linkedin-profile-posts-scraper").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 = { "url": "https://www.linkedin.com/showcase/linkedin-news/" } # Run the Actor and wait for it to finish run = client.actor("scraperoka/linkedin-profile-posts-scraper").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 '{ "url": "https://www.linkedin.com/showcase/linkedin-news/" }' | apify call scraperoka/linkedin-profile-posts-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scraperoka/linkedin-profile-posts-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Linkedin Profile Posts Scraper", "description": "🔎 LinkedIn Profile Posts Scraper extracts post content, engagement metrics, and author details from public LinkedIn profiles. 📈 Perfect for B2B research, lead gen, sentiment tracking & competitive insights—save time and scale your outreach.", "version": "1.0", "x-build-id": "sIKOMJgWCb9yLWHtr" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scraperoka~linkedin-profile-posts-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scraperoka-linkedin-profile-posts-scraper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scraperoka~linkedin-profile-posts-scraper/runs": { "post": { "operationId": "runs-sync-scraperoka-linkedin-profile-posts-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scraperoka~linkedin-profile-posts-scraper/run-sync": { "post": { "operationId": "run-sync-scraperoka-linkedin-profile-posts-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "url" ], "properties": { "url": { "title": "Url to check", "type": "string", "description": "The LinkedIn profile, showcase, or company URL to scrape posts from." }, "limit": { "title": "Maximum Posts per URL", "minimum": 1, "type": "integer", "description": "Maximum number of posts to scrape per provided URL.", "default": 20 } } }, "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 } } } } } } } } } } ```