# LinkedIn Following Exporter (`automationagents/linkedin-following-export`) Actor Export the profiles a LinkedIn account follows as structured data. Map interests and relationships for research. - **URL**: https://apify.com/automationagents/linkedin-following-export.md - **Developed by:** [Alex Jordan](https://apify.com/automationagents) (community) - **Categories:** Lead generation, Social media - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $1.70 / 1,000 result items This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. 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 Following Export LinkedIn Following Export extracts the profiles followed by the authenticated LinkedIn account. It returns structured records for followed accounts, including profile URLs, identifiers, names, profile images, headlines, job titles, and follower counts, which makes it useful for network analysis, audience mapping, and enrichment workflows. Built on the Apify platform, this Actor supports scheduling, webhooks, and dataset exports. ### Use cases - Export the accounts a LinkedIn user follows for network analysis - Build structured datasets of followed profiles for enrichment or CRM workflows - Review followed accounts for audience research, creator analysis, or prospecting - Run repeated following exports and compare changes over time ### How to use LinkedIn Following Export 1. Open the Actor on Apify 2. Enter the extraction limit and authenticated LinkedIn session fields 3. Start the run 4. Review the dataset output for followed-profile records ### Input This Actor accepts the fields required to export followed profiles through an authenticated LinkedIn session. ### Proxy object Use the proxy object to define how requests should be routed. Common fields are: - `ip` - Proxy host or endpoint URL - `port` - Proxy port - `username` - Proxy username - `password` - Proxy password ### Example input ```json { "maxCountLiFollowerExport": 10, "connectedAccountId": "example_connected_account_id", "profileId": "example-profile-id", "li_at": "example_li_at", "JSESSIONID": "ajax:example", "bcookie": "example_bcookie", "liap": "true", "li_theme_set": "app", "li_theme": "light", "timezone": "Asia/Calcutta", "bscookie": "example_bscookie", "user-agent": "Mozilla/5.0 ...", "timezoneOffset": "5.5", "csrf-token": "example_csrf-token", "User-Agent": "Mozilla/5.0 ...", "x-li-track": "{\"clientVersion\":\"1.13.455\"}", "x-li-lang": "en_US", "X-Restli-Protocol-Version": "2.0.0", "txSmSelfProfileUrl": "https://www.linkedin.com/in/example-self/", "proxy": { "ip": "http://proxy.example.com", "port": "1080", "username": "example_username", "password": "example_password" } } ```` ### Output The Actor writes the action result to the default dataset. ### Example output ```json { "success": true, "response": [ { "inputMaxCountLiFollowerExport": "5", "totalResultCount": 3, "fullName": "Rakshanda Kumawat", "firstName": "Rakshanda", "lastName": "Kumawat", "liProfileUrl": "https://www.linkedin.com/in/ACoAADZTLPwByBEikpxHin1R4UFNOShT4x7oinY?miniProfileUrn=urn%3Ali%3Afs_miniProfile%3AACoAADZTLPwByBEikpxHin1R4UFNOShT4x7oinY", "liProfileId": "ACoAADZTLPwByBEikpxHin1R4UFNOShT4x7oinY", "liMemberUrn": "911420668", "profileImageUrl": "https://media.licdn.com/dms/image/v2/D4D03AQHylmaFWFlLXQ/profile-displayphoto-shrink_100_100/profile-displayphoto-shrink_100_100/0/1686835274896", "headline": "Senior Human Resource Executive", "jobTitle": "Senior Human Resource Executive", "following": true, "followersCount": 21198, "timestamp": "2026-06-30T07:13:01.417Z" }, { "inputMaxCountLiFollowerExport": "5", "totalResultCount": 3, "fullName": "Anubhav Singh", "firstName": "Anubhav", "lastName": "Singh", "liProfileUrl": "https://www.linkedin.com/in/ACoAACeXACgBnBOA4a3SZc1nwsk3-eAWUtM938U?miniProfileUrn=urn%3Ali%3Afs_miniProfile%3AACoAACeXACgBnBOA4a3SZc1nwsk3-eAWUtM938U", "liProfileId": "ACoAACeXACgBnBOA4a3SZc1nwsk3-eAWUtM938U", "liMemberUrn": "664207400", "profileImageUrl": "https://media.licdn.com/dms/image/v2/D4D03AQELYUp1eP1w3w/profile-displayphoto-shrink_100_100/profile-displayphoto-shrink_100_100/0/1701001443243", "headline": "DM for referral, Salesforce Developer @Akamai || 5x Certified | LWC | Apex | Integration", "jobTitle": "DM for referral, Salesforce Developer @Akamai || 5x Certified | LWC | Apex | Integration", "following": true, "followersCount": 15959, "timestamp": "2026-06-30T07:13:01.418Z" } ] } ``` ### Pricing / Cost estimation $0.0017 per 50 result items. ### Support If you need adjustments for your workflow, use the Actor Issues tab or your internal support channel. # Actor input Schema ## `maxCountLiFollowerExport` (type: `integer`): Maximum number of followed profiles to extract. ## `texAuVariables` (type: `object`): Optional TexAu personalization variables. ## `connectedAccountId` (type: `string`): Connected LinkedIn account identifier. ## `profileId` (type: `string`): LinkedIn profile identifier for the signed-in account. ## `li_at` (type: `string`): LinkedIn li\_at cookie. ## `JSESSIONID` (type: `string`): LinkedIn JSESSIONID cookie. ## `bcookie` (type: `string`): LinkedIn browser cookie. ## `liap` (type: `string`): LinkedIn session field. ## `li_theme_set` (type: `string`): LinkedIn theme-set field. ## `li_theme` (type: `string`): LinkedIn theme field. ## `timezone` (type: `string`): Browser timezone. ## `bscookie` (type: `string`): LinkedIn browser secure cookie. ## `user-agent` (type: `string`): Lowercase user-agent field if required by runtime mapping. ## `timezoneOffset` (type: `string`): Browser timezone offset. ## `csrf-token` (type: `string`): CSRF token header value. ## `User-Agent` (type: `string`): Browser user agent string. ## `x-li-track` (type: `string`): LinkedIn tracking header value. ## `x-li-lang` (type: `string`): LinkedIn language header value. ## `X-Restli-Protocol-Version` (type: `string`): LinkedIn Rest.li protocol version. ## `txSmSelfProfileUrl` (type: `string`): TexAu self profile URL. ## `proxy` (type: `object`): Proxy object for browser session. ## Actor input object example ```json { "maxCountLiFollowerExport": 10, "texAuVariables": { "yourFirstName": "", "yourLastName": "", "yourJobTitle": "", "yourCompanyName": "", "yourCompanyDescription": "Example company description", "yourUsp": "Example USP" }, "connectedAccountId": "example_connected_account_id", "profileId": "example-profile-id", "li_at": "example_li_at", "JSESSIONID": "ajax:example", "bcookie": "example_bcookie", "liap": "true", "li_theme_set": "app", "li_theme": "light", "timezone": "Asia/Calcutta", "bscookie": "example_bscookie", "user-agent": "Mozilla/5.0 ...", "timezoneOffset": "5.5", "csrf-token": "example_csrf-token", "User-Agent": "Mozilla/5.0 ...", "x-li-track": "{\"clientVersion\":\"1.13.455\"}", "x-li-lang": "en_US", "X-Restli-Protocol-Version": "2.0.0", "txSmSelfProfileUrl": "https://www.linkedin.com/in/example-self/", "proxy": { "ip": "http://proxy.example.com", "port": "1080", "username": "example_username", "password": "example_password" } } ``` # Actor output Schema ## `results` (type: `string`): No description # 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 = { "maxCountLiFollowerExport": 10, "texAuVariables": { "yourFirstName": "", "yourLastName": "", "yourJobTitle": "", "yourCompanyName": "", "yourCompanyDescription": "Example company description", "yourUsp": "Example USP" }, "connectedAccountId": "example_connected_account_id", "profileId": "example-profile-id", "li_at": "example_li_at", "JSESSIONID": "ajax:example", "bcookie": "example_bcookie", "liap": "true", "li_theme_set": "app", "li_theme": "light", "timezone": "Asia/Calcutta", "bscookie": "example_bscookie", "user-agent": "Mozilla/5.0 ...", "timezoneOffset": "5.5", "csrf-token": "example_csrf-token", "User-Agent": "Mozilla/5.0 ...", "x-li-track": "{\"clientVersion\":\"1.13.455\"}", "x-li-lang": "en_US", "X-Restli-Protocol-Version": "2.0.0", "txSmSelfProfileUrl": "https://www.linkedin.com/in/example-self/", "proxy": { "ip": "http://proxy.example.com", "port": "1080", "username": "example_username", "password": "example_password" } }; // Run the Actor and wait for it to finish const run = await client.actor("automationagents/linkedin-following-export").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 = { "maxCountLiFollowerExport": 10, "texAuVariables": { "yourFirstName": "", "yourLastName": "", "yourJobTitle": "", "yourCompanyName": "", "yourCompanyDescription": "Example company description", "yourUsp": "Example USP", }, "connectedAccountId": "example_connected_account_id", "profileId": "example-profile-id", "li_at": "example_li_at", "JSESSIONID": "ajax:example", "bcookie": "example_bcookie", "liap": "true", "li_theme_set": "app", "li_theme": "light", "timezone": "Asia/Calcutta", "bscookie": "example_bscookie", "user-agent": "Mozilla/5.0 ...", "timezoneOffset": "5.5", "csrf-token": "example_csrf-token", "User-Agent": "Mozilla/5.0 ...", "x-li-track": "{\"clientVersion\":\"1.13.455\"}", "x-li-lang": "en_US", "X-Restli-Protocol-Version": "2.0.0", "txSmSelfProfileUrl": "https://www.linkedin.com/in/example-self/", "proxy": { "ip": "http://proxy.example.com", "port": "1080", "username": "example_username", "password": "example_password", }, } # Run the Actor and wait for it to finish run = client.actor("automationagents/linkedin-following-export").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 '{ "maxCountLiFollowerExport": 10, "texAuVariables": { "yourFirstName": "", "yourLastName": "", "yourJobTitle": "", "yourCompanyName": "", "yourCompanyDescription": "Example company description", "yourUsp": "Example USP" }, "connectedAccountId": "example_connected_account_id", "profileId": "example-profile-id", "li_at": "example_li_at", "JSESSIONID": "ajax:example", "bcookie": "example_bcookie", "liap": "true", "li_theme_set": "app", "li_theme": "light", "timezone": "Asia/Calcutta", "bscookie": "example_bscookie", "user-agent": "Mozilla/5.0 ...", "timezoneOffset": "5.5", "csrf-token": "example_csrf-token", "User-Agent": "Mozilla/5.0 ...", "x-li-track": "{\\"clientVersion\\":\\"1.13.455\\"}", "x-li-lang": "en_US", "X-Restli-Protocol-Version": "2.0.0", "txSmSelfProfileUrl": "https://www.linkedin.com/in/example-self/", "proxy": { "ip": "http://proxy.example.com", "port": "1080", "username": "example_username", "password": "example_password" } }' | apify call automationagents/linkedin-following-export --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=automationagents/linkedin-following-export", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Following Exporter", "description": "Export the profiles a LinkedIn account follows as structured data. Map interests and relationships for research.", "version": "0.1", "x-build-id": "31SSUaWhPfCwAz5Ql" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/automationagents~linkedin-following-export/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-automationagents-linkedin-following-export", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/automationagents~linkedin-following-export/runs": { "post": { "operationId": "runs-sync-automationagents-linkedin-following-export", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/automationagents~linkedin-following-export/run-sync": { "post": { "operationId": "run-sync-automationagents-linkedin-following-export", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "maxCountLiFollowerExport": { "title": "Limit", "type": "integer", "description": "Maximum number of followed profiles to extract." }, "texAuVariables": { "title": "TexAu Variables", "type": "object", "description": "Optional TexAu personalization variables." }, "connectedAccountId": { "title": "Connected Account ID", "type": "string", "description": "Connected LinkedIn account identifier." }, "profileId": { "title": "Profile ID", "type": "string", "description": "LinkedIn profile identifier for the signed-in account." }, "li_at": { "title": "li_at", "type": "string", "description": "LinkedIn li_at cookie." }, "JSESSIONID": { "title": "JSESSIONID", "type": "string", "description": "LinkedIn JSESSIONID cookie." }, "bcookie": { "title": "bcookie", "type": "string", "description": "LinkedIn browser cookie." }, "liap": { "title": "liap", "type": "string", "description": "LinkedIn session field." }, "li_theme_set": { "title": "li_theme_set", "type": "string", "description": "LinkedIn theme-set field." }, "li_theme": { "title": "li_theme", "type": "string", "description": "LinkedIn theme field." }, "timezone": { "title": "Timezone", "type": "string", "description": "Browser timezone." }, "bscookie": { "title": "bscookie", "type": "string", "description": "LinkedIn browser secure cookie." }, "user-agent": { "title": "user-agent", "type": "string", "description": "Lowercase user-agent field if required by runtime mapping." }, "timezoneOffset": { "title": "Timezone Offset", "type": "string", "description": "Browser timezone offset." }, "csrf-token": { "title": "csrf-token", "type": "string", "description": "CSRF token header value." }, "User-Agent": { "title": "User-Agent", "type": "string", "description": "Browser user agent string." }, "x-li-track": { "title": "x-li-track", "type": "string", "description": "LinkedIn tracking header value." }, "x-li-lang": { "title": "x-li-lang", "type": "string", "description": "LinkedIn language header value." }, "X-Restli-Protocol-Version": { "title": "X-Restli-Protocol-Version", "type": "string", "description": "LinkedIn Rest.li protocol version." }, "txSmSelfProfileUrl": { "title": "Self Profile URL", "type": "string", "description": "TexAu self profile URL." }, "proxy": { "title": "Proxy", "type": "object", "description": "Proxy object for browser session." } } }, "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 } } } } } } } } } } ```