# LinkedIn Post Reactions Scraper - \[✅ No Cookies] (`khadinakbar/linkedin-post-reactions-scraper`) Actor Extract public LinkedIn post reaction metrics, like counts, comment counts, share counts, engagement totals, and visible reactor profile rows when provider payloads expose them. - **URL**: https://apify.com/khadinakbar/linkedin-post-reactions-scraper.md - **Developed by:** [Khadin Akbar](https://apify.com/khadinakbar) (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 $8.00 / 1,000 linkedin post reactions scrapeds 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 Post Reactions Scraper Extract public reaction and engagement metrics from known LinkedIn post URLs without asking users for LinkedIn cookies. This Actor is designed for lead research, campaign monitoring, creator analytics, and AI-agent workflows that need clean JSON from public LinkedIn posts. It uses owner-managed public-data providers, tries ScrapeCreators first by default, and falls back to SociaVault when configured. ### What You Get - One reaction summary row per LinkedIn post - Like and total reaction counts when exposed - Comment, share, and engagement totals - Reaction breakdowns by type when exposed by the provider - Post author, author URL, follower count, title, text, and publish date when available - Optional visible reactor profile rows if a provider payload includes reactor identities - `OUTPUT` and `RUN_SUMMARY` records for automation, monitoring, and AI agents ### Important Data Boundary Public LinkedIn provider endpoints currently expose post-level reaction counts more reliably than the full list of people who reacted. The default `summaries` mode saves reaction metrics for each post. The `reactors` and `both` modes normalize visible reactor profile objects only when the upstream provider includes them in the public post payload. The Actor does not use LinkedIn login cookies, does not access private posts, and does not promise private member data, emails, connections, or a complete LinkedIn-native reactions graph. ### Input Provide LinkedIn post URLs through `startUrls` or `postUrls`. Numeric activity IDs and `urn:li:activity` values are also accepted. ```json { "postUrls": [ "https://www.linkedin.com/feed/update/urn:li:activity:7312345678901234567/" ], "outputMode": "summaries", "maxPosts": 100, "maxReactors": 5000 } ```` ### Output Example ```json { "recordType": "post", "postUrl": "https://www.linkedin.com/pulse/being-father-has-made-me-better-leader-vice-versa-austen-allred/", "postTitle": "Being a Father Has Made me a Better Leader, and Vice Versa", "postAuthorName": "Austen Allred", "postAuthorUrl": "https://www.linkedin.com/in/austenallred", "postPublishedAt": "2020-06-21T14:35:59.000+00:00", "likeCount": 215, "reactionCount": 215, "commentCount": 17, "engagementCount": 232, "reactorProfilesFound": 0, "reactorProfilesSaved": 0, "source": "sociavault", "scrapedAt": "2026-06-10T00:00:00.000Z" } ``` ### Output Modes - `summaries`: saves post-level reaction and engagement metrics. Recommended. - `reactors`: saves visible reactor profile rows only when the provider exposes identities. - `both`: saves both summary rows and visible reactor rows. ### Provider Setup Set at least one owner secret in Apify Console: ```bash apify secrets add SCRAPECREATORS_API_KEY "your-key" apify secrets add SOCIAVAULT_API_KEY "your-key" ``` `SOCIALVAULT_API_KEY` is also read for compatibility with older actors, but `SOCIAVAULT_API_KEY` is preferred. ### Pricing This Actor uses pay-per-event pricing: - Actor start: `$0.00005` - Post reaction summary row: `$0.008` - Visible reactor profile row: `$0.012` Platform usage is paid by the user. You can cap run spend with Apify's max charge settings. ### Use Cases - Measure reaction volume on LinkedIn launch posts - Monitor thought-leader or competitor post engagement - Enrich CRM workflows with public post engagement signals - Track campaign performance across known LinkedIn posts - Feed AI agents structured engagement metrics from public post URLs ### Limitations - Results depend on public/provider-visible LinkedIn data. - Public post endpoints may return aggregate reaction counts without reactor identities. - LinkedIn can change public page structure and provider response fields. - Private, deleted, restricted, or login-only posts may return no data. ### Support If a public post URL returns no results, include the run ID, the input URL, selected provider order, and the `RUN_SUMMARY` record when reporting the issue. # Actor input Schema ## `startUrls` (type: `array`): LinkedIn post, feed update, article, or company post URLs to inspect. ## `postUrls` (type: `array`): Optional line-separated list of LinkedIn post URLs, numeric activity IDs, or urn:li:activity values. ## `maxPosts` (type: `integer`): Maximum number of unique post URLs to process. ## `maxReactors` (type: `integer`): Maximum number of visible reactor profile rows to save if the provider exposes reactor identities. Reaction summary rows are still saved even when no reactor identities are exposed. ## `outputMode` (type: `string`): Choose post reaction summary rows, visible reactor profile rows, or both. Summary rows are recommended because public provider endpoints currently expose counts more reliably than reactor identities. ## `providerOrder` (type: `string`): Choose which managed public-data provider to try first. ## `includeRawData` (type: `boolean`): Attach raw provider post or reaction objects to dataset rows for debugging. This increases dataset size. ## Actor input object example ```json { "startUrls": [ { "url": "https://www.linkedin.com/pulse/being-father-has-made-me-better-leader-vice-versa-austen-allred/" } ], "postUrls": [], "maxPosts": 100, "maxReactors": 5000, "outputMode": "summaries", "providerOrder": "scrapecreators-first", "includeRawData": false } ``` # Actor output Schema ## `dataset` (type: `string`): Structured dataset records with reaction counts, engagement metrics, author details, provider source, and optional visible reactor profile rows. ## `datasetCsv` (type: `string`): CSV export of the same LinkedIn post reaction dataset records. ## `runSummary` (type: `string`): Machine-readable telemetry with posts processed, rows saved, providers used, provider status codes, costs, warnings, and stop reason. ## `outputSummary` (type: `string`): Compact agent-friendly summary with rows saved, posts processed, providers used, warnings, and dataset URL. # 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": [ { "url": "https://www.linkedin.com/pulse/being-father-has-made-me-better-leader-vice-versa-austen-allred/" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("khadinakbar/linkedin-post-reactions-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 = { "startUrls": [{ "url": "https://www.linkedin.com/pulse/being-father-has-made-me-better-leader-vice-versa-austen-allred/" }] } # Run the Actor and wait for it to finish run = client.actor("khadinakbar/linkedin-post-reactions-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 '{ "startUrls": [ { "url": "https://www.linkedin.com/pulse/being-father-has-made-me-better-leader-vice-versa-austen-allred/" } ] }' | apify call khadinakbar/linkedin-post-reactions-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=khadinakbar/linkedin-post-reactions-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Post Reactions Scraper - [✅ No Cookies]", "description": "Extract public LinkedIn post reaction metrics, like counts, comment counts, share counts, engagement totals, and visible reactor profile rows when provider payloads expose them.", "version": "0.1", "x-build-id": "WQT85k3f8xQSxAA7U" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/khadinakbar~linkedin-post-reactions-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-khadinakbar-linkedin-post-reactions-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/khadinakbar~linkedin-post-reactions-scraper/runs": { "post": { "operationId": "runs-sync-khadinakbar-linkedin-post-reactions-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/khadinakbar~linkedin-post-reactions-scraper/run-sync": { "post": { "operationId": "run-sync-khadinakbar-linkedin-post-reactions-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "startUrls": { "title": "LinkedIn post URLs", "type": "array", "description": "LinkedIn post, feed update, article, or company post URLs to inspect.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "postUrls": { "title": "Post URLs, activity IDs, or URNs", "type": "array", "description": "Optional line-separated list of LinkedIn post URLs, numeric activity IDs, or urn:li:activity values.", "default": [], "items": { "type": "string" } }, "maxPosts": { "title": "Maximum posts", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum number of unique post URLs to process.", "default": 100 }, "maxReactors": { "title": "Maximum reactor rows", "minimum": 0, "maximum": 50000, "type": "integer", "description": "Maximum number of visible reactor profile rows to save if the provider exposes reactor identities. Reaction summary rows are still saved even when no reactor identities are exposed.", "default": 5000 }, "outputMode": { "title": "Output mode", "enum": [ "summaries", "reactors", "both" ], "type": "string", "description": "Choose post reaction summary rows, visible reactor profile rows, or both. Summary rows are recommended because public provider endpoints currently expose counts more reliably than reactor identities.", "default": "summaries" }, "providerOrder": { "title": "Provider order", "enum": [ "scrapecreators-first", "sociavault-first", "scrapecreators-only", "sociavault-only" ], "type": "string", "description": "Choose which managed public-data provider to try first.", "default": "scrapecreators-first" }, "includeRawData": { "title": "Include raw provider data", "type": "boolean", "description": "Attach raw provider post or reaction objects to dataset rows for debugging. This increases dataset size.", "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 } } } } } } } } } } ```