Pricing

Pay per usage

Linkedin Post Reactions Scraper

Scrape LinkedIn post reaction data instantly with this LinkedIn Post Reactions Scraper 👍 Extract usernames, reaction types, profile links, and engagement insights with ease 📊 Perfect for audience analysis, lead generation, competitor research, and social selling 🔍🚀

Pricing

Pay per usage

Rating

0.0

(0)

Developer

Scrapio

Actor stats

Bookmarked

Total users

Monthly active users

20 days ago

Last modified

Categories

Automation

Jobs

Lead generation

You can access the Linkedin Post Reactions Scraper programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.

Python

JavaScript

CLI

OpenAPI

HTTP

MCP

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        "type": "object",
        "properties": {
          "posts": {
            "title": "📋 Posts to scrape",
            "type": "array",
            "description": "🔗 Add one or more LinkedIn post links. Works with /posts/... URLs and /feed/update/urn:li:activity:... links. Use + Add for more rows or Bulk edit to paste many at once.",
            "items": {
              "type": "string"
            }
          },
          "maxItems": {
            "title": "🔢 Max reactions per post",
            "minimum": 1,
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            "type": "integer",
            "description": "Number of reactors to collect per post (1–5000). Increase for more data; larger values take longer.",
            "default": 50
          },
          "reactionTypeFilter": {
            "title": "👍 Reaction type",
            "enum": [
              "",
              "ALL",
              "LIKE",
              "PRAISE",
              "EMPATHY",
              "APPRECIATION",
              "INTEREST",
              "ENTERTAINMENT"
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            "type": "string",
            "description": "Filter by one reaction type or get all. Leave as “Select...” or pick “All reaction types” to include every reaction.",
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          },
          "profileScraperMode": {
            "title": "👤 Profile detail level",
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              "short",
              "main"
            ],
            "type": "string",
            "description": "Short: free, basic reactor info. Main: full profile details without opening sections ($0.002 per profile).",
            "default": "short"
          },
          "liAtCookie": {
            "title": "🍪 LinkedIn li_at cookie",
            "type": "string",
            "description": "Paste your LinkedIn session cookie (li_at) so the actor can access reactions. Copy from browser: DevTools → Application → Cookies → linkedin.com → li_at. Needed for the scraper to run."
          },
          "proxyConfiguration": {
            "title": "🌐 Proxy",
            "type": "object",
            "description": "Leave default for no proxy. If LinkedIn blocks, the actor will try datacenter then residential proxy (with retries) and stay on residential. Each step is logged."
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        }
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                "type": "string"
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                  "origin": {
                    "type": "string",
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                  },
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                    "type": "string"
                  }
                }
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Linkedin Post Reactions Scraper OpenAPI definition

OpenAPI is a standard for designing and describing RESTful APIs, allowing developers to define API structure, endpoints, and data formats in a machine-readable way. It simplifies API development, integration, and documentation.

OpenAPI is effective when used with AI agents and GPTs by standardizing how these systems interact with various APIs, for reliable integrations and efficient communication.

By defining machine-readable API specifications, OpenAPI allows AI models like GPTs to understand and use varied data sources, improving accuracy. This accelerates development, reduces errors, and provides context-aware responses, making OpenAPI a core component for AI applications.

You can download the OpenAPI definitions for Linkedin Post Reactions Scraper from the options below:

OpenAPI.json

If you’d like to learn more about how OpenAPI powers GPTs, read our blog post.

You can also check out our other API clients:

Linkedin Post Reactions Scraper API in Python

Linkedin Post Reactions Scraper API in JavaScript

Linkedin Post Reactions Scraper API through CLI

Linkedin Post Reactions Scraper API

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👍 LinkedIn Post Reactions Scraper captures who reacted to any post—names, titles, profile URLs & reaction types (Like, Celebrate, Support, etc.). 📊 Export to CSV/JSON for engagement analysis, lead lists & outreach. ⚙️ Perfect for social proof, community growth & competitor research.

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