# LinkedIn Related User Scraper (`thenetaji/linkedin-related-user-scraper`) Actor Extract related LinkedIn profile suggestions from one or more seed profiles, with optional full profile enrichment for each related user. - **URL**: https://apify.com/thenetaji/linkedin-related-user-scraper.md - **Developed by:** [The Netaji](https://apify.com/thenetaji) (community) - **Categories:** Social media, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $1.50 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 Related User Scraper extracts related LinkedIn profile suggestions from seed profiles and can enrich each related user with full public profile data.** Use it when you need structured related profile suggestions from LinkedIn inside Apify datasets. Provide one or more usernames or profile URLs, set a result limit, and optionally enable enrichment for full profile details. It is designed for lead discovery, recruiting research, professional network mapping, market research, and AI workflows that need repeatable LinkedIn-related profile data. ### What is LinkedIn? LinkedIn is a professional networking platform where public profiles can show work history, education, articles, activity, and related people suggestions. ### What data can I extract with LinkedIn Related User Scraper? LinkedIn Related User Scraper extracts the following data from LinkedIn: - **Related profile identity** - Names, LinkedIn profile URLs, usernames, and headline text from the related profile block. - **Discovery context** - The seed username, seed profile URL, and seed profile name that produced each related profile. - **Enriched profile details** - When enrichment is enabled, each related profile can include full public profile data such as location, about text, work history, education, articles, activity, and structured profile metadata. Use maxItems to keep test runs small, then enable enrichment when you need full profile details for every related user. ### How can I use LinkedIn data? - **Lead discovery** - Start from a known founder, executive, recruiter, investor, or creator and collect adjacent LinkedIn profiles for outreach research. - **Professional network mapping** - Build datasets that show which people LinkedIn suggests around a known public profile. - **Recruiting research** - Find profiles related to a target candidate, hiring manager, or company leader and enrich the most relevant results. - **Market and audience research** - Discover professionals clustered around an industry profile, then export the dataset for analysis. - **AI enrichment workflows** - Feed related profile records into ranking, classification, CRM enrichment, or research agents. ### How to scrape LinkedIn #### Step 1: Enter seed profiles Add one or more LinkedIn usernames or /in/ profile URLs to the username array. #### Step 2: Set the result limit Use maxItems to control how many related profiles are saved across all seed profiles. #### Step 3: Choose enrichment Leave Enrich profiles off for lightweight related profile records, or turn it on to attach the full public profile object. #### Step 4: Run and export Start the Actor and download the Apify dataset as JSON, CSV, Excel, XML, or HTML. ### LinkedIn Related User Scraper features - **Related LinkedIn profiles** - Extract the people shown in the related profiles block for one or more seed LinkedIn users. - **Optional profile enrichment** - Fetch full public profile details for every related user and attach them to the dataset record. - **Multiple seed profiles** - Provide one or more LinkedIn usernames or profile URLs and collect related users across all of them. - **Result limits and deduplication** - Use maxItems to control run size while duplicate related profiles are skipped across seed profiles. - **Apify-ready exports** - Results are saved to the default Apify dataset and can be downloaded as JSON, CSV, Excel, XML, or HTML. Built for reliable Apify runs with automatic retries, proxy support, and structured dataset output. ### Input Configure the run on the Actor's Input tab. Set the fields for your chosen mode, then start the run. #### Related profiles Enter one or more LinkedIn usernames or /in/ profile URLs and collect profiles shown as related to those seeds. | Field | Type | Required | Description | | --- | --- | --- | --- | | `username` | array | Yes | Seed LinkedIn profile usernames or /in/ profile URLs to find related profiles for. | | `maxItems` | integer | No | Maximum number of related profiles to save across all seed profiles. Set 0 for unlimited. | | `enrichProfile` | boolean | No | Fetch the full LinkedIn profile for each related profile and attach it under profile. | #### Related profiles with enrichment Enable Enrich profiles to attach the full public profile object for each related user. | Field | Type | Required | Description | | --- | --- | --- | --- | | `username` | array | Yes | Seed LinkedIn profile usernames or /in/ profile URLs to find related profiles for. | | `maxItems` | integer | No | Maximum number of related profiles to save across all seed profiles. Set 0 for unlimited. | | `enrichProfile` | boolean | No | Fetch the full LinkedIn profile for each related profile and attach it under profile. | #### Example input ```json { "username": [ "williamhgates" ], "maxItems": 20, "enrichProfile": false } ```` ### Output Download results as JSON, CSV, Excel, XML, or HTML, or pull them from the Apify Dataset API. #### Related profile | Field | Type | Description | | --- | --- | --- | | `name` | string,number,boolean,object,array,null | Name shown on the related LinkedIn profile. | | `headline` | string,number,boolean,object,array,null | Current headline or organization text shown for the related profile. | | `username` | string,number,boolean,object,array,null | LinkedIn username extracted from the related profile URL. | | `url` | string,number,boolean,object,array,null | LinkedIn profile URL for the related profile. | #### Discovery source | Field | Type | Description | | --- | --- | --- | | `source_username` | string,number,boolean,object,array,null | Seed LinkedIn username whose profile suggested this related profile. | | `source_name` | string,number,boolean,object,array,null | Seed profile name whose related profile block contained this result. | | `source_url` | string,number,boolean,object,array,null | LinkedIn URL of the seed profile. | #### Enrichment | Field | Type | Description | | --- | --- | --- | | `enriched` | string,number,boolean,object,array,null | Whether a full profile was successfully attached. | | `profile` | string,number,boolean,object,array,null | Full LinkedIn profile data when enrichment is enabled. | #### Example output ```json { "name": "Melinda French Gates", "headline": "Pivotal", "url": "https://www.linkedin.com/in/melindagates", "username": "melindagates", "source_username": "williamhgates", "source_name": "Bill Gates", "source_url": "https://www.linkedin.com/in/williamhgates", "enriched": false } ``` ### How much does it cost to scrape LinkedIn? This Actor uses Apify pay-per-result pricing. You are charged for successful dataset results according to the Actor pricing shown on the Apify Pricing tab. Enrichment may add extra billable events when enabled. Apify's free plan includes monthly credits, which may cover small test runs and up to the free result allowance configured for the Actor. Start with a low maxItems value before enabling enrichment for large seed lists. ### How does LinkedIn Related User Scraper compare to other LinkedIn scrapers? | Tool | Price / 1K | Fields | Key difference | | --- | --- | --- | --- | | LinkedIn Related User Scraper (this Actor) | Apify pay-per-result | Related profile name, headline, URL, username, source profile, optional full profile object | Focused on collecting related LinkedIn people suggestions from seed profiles and optionally enriching each result. | | Manual LinkedIn browsing | Manual time | Whatever you copy by hand | Slow, inconsistent, and hard to repeat across seed profiles. | - Best when you want lookalike or adjacent LinkedIn profiles starting from known people. - Use manual browsing only for one-off checks, not repeatable datasets. ### LinkedIn Related User Scraper FAQ #### Can I provide LinkedIn profile URLs instead of usernames? Yes. The Actor accepts either LinkedIn usernames such as williamhgates or public profile URLs such as https://www.linkedin.com/in/williamhgates. #### What does Enrich profiles do? When enabled, the Actor fetches the full public profile for each related user and stores it under the profile field. Leave it off for faster, lighter runs. #### Can I scrape related profiles for multiple seed users? Yes. Add multiple usernames or profile URLs to the username array. The Actor processes them in order and skips duplicate related profiles. #### How do I control run cost? Set maxItems to a small number while testing. Enable enrichment only when you need full profile details for each related user. #### Can I export LinkedIn related profiles to CSV or Excel? Yes. Apify datasets can be downloaded as JSON, CSV, Excel, XML, HTML, or accessed through the Dataset API. #### Can I schedule recurring LinkedIn related profile collection? Yes. Use Apify schedules to run the Actor hourly, daily, weekly, or at any custom interval supported by Apify. ### Can I integrate LinkedIn Related User Scraper with other apps? Yes. LinkedIn Related User Scraper works with Apify integrations and can send results to common automation, spreadsheet, database, and AI workflows. - **Google Sheets and Airtable** - Export related profile lists into shared research tables. - **CRM and enrichment workflows** - Send related profile records into lead scoring, enrichment, or recruiting pipelines. - **Make, Zapier, and n8n** - Trigger downstream automations when a scrape finishes. - **Apify API and webhooks** - Run the Actor from code and consume completed datasets programmatically. - **Apify MCP Server** - Let AI agents pull fresh LinkedIn related profile data through Apify. ### Can I use LinkedIn Related User Scraper with the Apify API? Yes. LinkedIn Related User Scraper can be run programmatically with the Apify API. You can also schedule recurring runs, trigger runs with webhooks, and export data through the Dataset API. #### Python ```python from apify_client import ApifyClient client = ApifyClient("YOUR_APIFY_API_TOKEN") run = client.actor("thenetaji/linkedin-related-user-scraper").call(run_input={ "username": [ "williamhgates" ], "maxItems": 20, "enrichProfile": false }) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) ``` #### Node.js ```javascript import { ApifyClient } from "apify-client"; const client = new ApifyClient({ token: "YOUR_APIFY_API_TOKEN" }); const run = await client.actor("thenetaji/linkedin-related-user-scraper").call({ "username": [ "williamhgates" ], "maxItems": 20, "enrichProfile": false }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); console.log(items); ``` ### Can I use LinkedIn Related User Scraper through an MCP server? Yes. AI agents can call this Actor through the Apify MCP server. Point your MCP client at the Apify MCP server (https://mcp.apify.com) and enable the Actor as a tool so agents can pull fresh LinkedIn related profile data on demand. ### Is it legal to scrape LinkedIn? This Actor extracts publicly available LinkedIn profile information. It should not be used to collect private account data, bypass access controls, or contact people in ways that violate privacy laws, LinkedIn terms, or your own compliance obligations. If you are unsure, consult a qualified lawyer. ### Your feedback Use the Issues tab on the Actor page for bug reports, missing fields, and feature requests. ### You might also like - [Instagram related user scraper](https://apify.com/thenetaji/instagram-related-user-scraper) - Extract related Instagram users with optional profile enrichment. - [LinkedIn Profile Scraper](https://apify.com/apify/linkedin-profile-scraper) - Collect structured public LinkedIn profile data. - [LinkedIn Company Scraper](https://apify.com/apify/linkedin-company-scraper) - Extract public LinkedIn company profile data. *Last updated:* 2026-07-10 *Keywords:* LinkedIn Related User Scraper, LinkedIn related profiles scraper, LinkedIn similar profiles scraper, scrape LinkedIn related users, LinkedIn lead discovery, LinkedIn profile enrichment, LinkedIn people scraper, LinkedIn network research # Actor input Schema ## `username` (type: `array`): Seed LinkedIn profile usernames or /in/ profile URLs to find related profiles for. ## `maxItems` (type: `integer`): Maximum number of related profiles to save across all seed profiles. Set 0 for unlimited. ## `enrichProfile` (type: `boolean`): Fetch the full LinkedIn profile for each related profile and attach it under profile. ## Actor input object example ```json { "username": [ "williamhgates" ], "maxItems": 20, "enrichProfile": false } ``` # Actor output Schema ## `dataset` (type: `string`): Dataset containing all scraped data # 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 = { "username": [ "williamhgates" ], "maxItems": 20 }; // Run the Actor and wait for it to finish const run = await client.actor("thenetaji/linkedin-related-user-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 = { "username": ["williamhgates"], "maxItems": 20, } # Run the Actor and wait for it to finish run = client.actor("thenetaji/linkedin-related-user-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 '{ "username": [ "williamhgates" ], "maxItems": 20 }' | apify call thenetaji/linkedin-related-user-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=thenetaji/linkedin-related-user-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Related User Scraper", "description": "Extract related LinkedIn profile suggestions from one or more seed profiles, with optional full profile enrichment for each related user.", "version": "0.1", "x-build-id": "iwLjBqVfwJV8Zz3OE" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/thenetaji~linkedin-related-user-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-thenetaji-linkedin-related-user-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/thenetaji~linkedin-related-user-scraper/runs": { "post": { "operationId": "runs-sync-thenetaji-linkedin-related-user-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/thenetaji~linkedin-related-user-scraper/run-sync": { "post": { "operationId": "run-sync-thenetaji-linkedin-related-user-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "username" ], "properties": { "username": { "title": "LinkedIn usernames", "type": "array", "description": "Seed LinkedIn profile usernames or /in/ profile URLs to find related profiles for.", "items": { "type": "string" }, "default": [ "williamhgates" ] }, "maxItems": { "title": "Max results", "minimum": 0, "type": "integer", "description": "Maximum number of related profiles to save across all seed profiles. Set 0 for unlimited.", "default": 100 }, "enrichProfile": { "title": "Enrich profiles", "type": "boolean", "description": "Fetch the full LinkedIn profile for each related profile and attach it under profile.", "default": false } } }, "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 } } } } } } } } } } ```