# Facebook Post Engagement Scraper ⚡ | Lightweight Metrics (`premiumscraper/facebook-post-engagement-scraper-lightweight-metrics`) Actor Extract lightweight engagement metrics from Facebook posts. Output includes: total reactions, comment count, share count, video view count, per-type reaction breakdown (Like/Love/Haha/Wow/Sad/Angry), and calculated engagement rate. One row per post ✨ Facebook Post Engagement Scraper⚡ - **URL**: https://apify.com/premiumscraper/facebook-post-engagement-scraper-lightweight-metrics.md - **Developed by:** [Premium Scraper](https://apify.com/premiumscraper) (community) - **Categories:** Social media, Developer tools, Automation - **Stats:** 5 total users, 4 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $2.00 / 1,000 engagement row scrapeds This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 ## Facebook Post Engagement Scraper ⚡ — Lightweight Engagement Metrics Extract **Facebook engagement** metrics from any public Facebook post URL. This Facebook engagement scraper returns one lightweight row per post with reactions, comments, shares, views, and a calculated Facebook engagement rate — no full post body, no media downloads. ### 🤔 Why Use This Facebook Engagement Scraper? When you need Facebook engagement numbers fast — without the overhead of full post data, comment trees, or media downloads — this Facebook engagement scraper delivers exactly what you need. One flat row per post with every Facebook engagement metric Facebook exposes publicly. Perfect for Facebook engagement dashboards, content performance tracking, and Facebook engagement benchmarking. ### ⚙️ How This Facebook Engagement Scraper Works 1️⃣ **Provide input** — enter Facebook post, video, photo, or share URLs (and/or usernames). 2️⃣ **Post resolution** — the Facebook engagement scraper resolves each URL and fetches the post metadata. 3️⃣ **Facebook engagement extraction** — reaction count, comment count, share count, video views, and reaction breakdown are parsed. 4️⃣ **Rate calculation** — a Facebook engagement rate proxy is calculated as (reactions + comments + shares) / views × 100 for video posts. 5️⃣ **Flat output** — one row per post with all Facebook engagement metrics. 6️⃣ **Billing** — you are charged per Facebook engagement row, and the run stops at your budget cap. ### 📦 What Facebook Engagement Data Does This Actor Extract? For each post URL, this Facebook engagement scraper returns: - ✅ **Facebook engagement reaction count** — total reactions (exact integer) - ✅ **Facebook engagement reaction breakdown** — per-type counts (Like, Love, Haha, Wow, Sad, Angry) - ✅ **Facebook engagement comment count** — total comments - ✅ **Facebook engagement share count** — total shares - ✅ **Facebook engagement video views** — view count for video posts - ✅ **Facebook engagement rate proxy** — (reactions + comments + shares) / views × 100 for video posts - ✅ **Total Facebook engagement** — combined reactions + comments + shares - ✅ **Post metadata** — post ID, permalink, creation time, author info ### ⚙️ Input Configuration | Field | Type | Default | Description | |-------|------|---------|-------------| | `username` | string[] | — | Facebook usernames (e.g., `Cristiano`, `nike`) | | `facebook_urls` | URL[] | — | Direct Facebook post, video, photo, or share URLs | You can mix usernames and URLs. Duplicates are skipped automatically. ### 📊 Output Dataset — Facebook Engagement Fields Each row is one post's Facebook engagement summary: | Field | Type | Description | |-------|------|-------------| | `type` | string | Always `engagement_row` | | `number` | integer | Sequential row number | | `source_post_url` | string | Original input URL | | `post_id` | string | Post identifier | | `permalink_url` | string | Canonical post URL | | `created_at` | string | Post creation timestamp | | `profile_name` | string | Post author name | | `profile_id` | string | Post author ID | | `profile_url` | string | Post author profile URL | | `profile_is_verified` | boolean | Author verification status | | `reaction_count_total` | integer | Total Facebook engagement reactions | | `reaction_count_reduced` | string | Facebook engagement reactions (display text) | | `comment_count_total` | integer | Total Facebook engagement comments | | `comment_count_reduced` | string | Facebook engagement comments (display text) | | `share_count_total` | integer | Total Facebook engagement shares | | `share_count_reduced` | string | Facebook engagement shares (display text) | | `video_view_count_total` | integer | Facebook engagement video views | | `top_reaction_types` | array | Facebook engagement reaction type names | | `top_reaction_labels` | array | Facebook engagement reaction labels | | `top_reactions_breakdown` | array | Per-type Facebook engagement reaction counts | | `total_engagement` | integer | Combined Facebook engagement (reactions + comments + shares) | | `engagement_rate_proxy` | number | Facebook engagement rate = total / views × 100 | | `has_video` | boolean | Whether the post contains video | | `attachment_types` | array | Post attachment types | ### 📋 Sample Output ```json { "type": "engagement_row", "number": 1, "source_post_url": "https://www.facebook.com/Cristiano/posts/pfbid0...", "post_id": "pfbid0...", "permalink_url": "https://www.facebook.com/Cristiano/posts/pfbid0...", "created_at": "2025-12-15T10:00:00+0000", "profile_name": "Cristiano Ronaldo", "reaction_count_total": 850000, "comment_count_total": 12000, "share_count_total": 5000, "video_view_count_total": 15000000, "total_engagement": 867000, "engagement_rate_proxy": 5.78, "top_reactions_breakdown": [ { "type": "LIKE", "count": 500000 }, { "type": "LOVE", "count": 250000 }, { "type": "HAHA", "count": 50000 } ] } ```` ### 💲 Facebook Engagement Pricing Pay-Per-Event: **$0.001 per Facebook engagement row** (~$1 per 1,000 posts). Set a **Maximum Cost Per Run** to cap spending. The actor stops gracefully at the budget limit. | Posts Scraped | Estimated Cost | |--------------|----------------| | 100 posts | $0.10 | | 500 posts | $0.50 | | 1,000 posts | $1.00 | | 10,000 posts | $10.00 | ### 🎯 Facebook Engagement Use Cases - 📊 **Facebook engagement dashboards** — Build real-time Facebook engagement tracking - 🔍 **Content performance** — Compare Facebook engagement across posts and pages - 🛡️ **Facebook engagement benchmarking** — Benchmark Facebook engagement rates against industry averages - 📈 **A/B testing** — Measure Facebook engagement impact of different content strategies - 🎯 **Viral detection** — Identify posts with exceptional Facebook engagement spikes - 💼 **Influencer analytics** — Calculate Facebook engagement rates for creator evaluation - 🧠 **Reporting** — Generate Facebook engagement reports for clients or stakeholders - 📢 **Trend monitoring** — Track Facebook engagement trends over time for specific pages ### 💡 Tips & Best Practices - ✅ **Use for metrics only** — this Facebook engagement scraper is optimized for numbers. For full post text or comments, use the dedicated Post or Comments scrapers. - 💰 **Compare `engagement_rate_proxy`** — this field lets you benchmark Facebook engagement across posts with different view counts. - 🔧 **Video posts are best** — Facebook engagement rate is most meaningful for video posts that have a view count. - 📌 **Budget cap** — set a Maximum Cost Per Run for large Facebook engagement scraping batches. - ⏱️ **Schedule runs** — set up periodic Facebook engagement tracking to monitor content performance over time. ### ❓ Frequently Asked Questions **Q: What is `engagement_rate_proxy`?** A: It's calculated as (reactions + comments + shares) / video views × 100. Only meaningful for video posts with view counts. **Q: Does this scraper get the full post text?** A: No. This Facebook engagement scraper focuses on metrics only. For full post data, use the main Posts Scraper. **Q: Can I track Facebook engagement over time?** A: Yes. Schedule recurring runs and compare the Facebook engagement numbers for the same post URLs across runs. **Q: Why are some Facebook engagement fields zero?** A: Some posts have no video views (non-video posts) or no shares. Zero is a valid Facebook engagement value. ### ⚠️ Limitations - ⛔ **Public posts only** — this Facebook engagement scraper cannot access engagement data on private or friends-only posts. - ⛔ **No post text** — this actor focuses on Facebook engagement metrics. For full post text and media, use the main Posts Scraper. - ⛔ **Facebook engagement rate requires views** — `engagement_rate_proxy` is only meaningful for video posts with view counts. - ⛔ **Rate limits** — scraping a very large number of posts for Facebook engagement data may trigger rate-limiting. - ⛔ **Snapshot in time** — Facebook engagement numbers change as users continue to interact. Values reflect the moment of scraping. ### 📤 Output Format Tips - 📁 **JSON** — default Apify dataset format. Each Facebook engagement row is a JSON object. - 📁 **CSV** — export via the Apify console for spreadsheet-ready Facebook engagement data. - 📁 **Excel** — download directly from the Apify dataset tab. - 📁 **API access** — retrieve Facebook engagement data programmatically via the Apify dataset API endpoint. - 📁 **Webhook** — trigger downstream workflows when the Facebook engagement scraping run finishes. ### 🔌 Integration Ideas - 📊 Feed Facebook engagement data into dashboards (Looker Studio, Tableau, Google Sheets). - 🔗 Set up alerts when Facebook engagement on a post exceeds a threshold. - ⏰ Compare Facebook engagement across campaigns by tagging post URLs. - 🔄 Combine with Reactions Scraper for per-type Facebook engagement sentiment breakdown. - 📡 Connect via Apify integrations to Slack, Zapier, or Make for automated Facebook engagement alerts. - 💾 Store Facebook engagement snapshots over time to build historical performance charts. - 🤖 Use Facebook engagement data to power content-recommendation engines. ### 🔒 Privacy & Compliance This Facebook engagement scraper only accesses publicly visible Facebook engagement data. No authentication is required. The actor does not bypass any access controls. All internal tokens and proxy connection data are redacted from logs. Users are responsible for ensuring their use of Facebook engagement data complies with applicable laws and Facebook's terms of service. # Actor input Schema ## `username` (type: `array`): Enter one or more Facebook usernames such as Cristiano or nike. ## `facebook_urls` (type: `array`): One or more direct Facebook post, video, photo, or share URLs. ## Actor input object example ```json { "username": [ "Cristiano" ], "facebook_urls": [ { "url": "https://www.facebook.com/Cristiano/posts/pfbid0Dp9Wrmv1NAkFX1nSkKwLEKftjMSHbDYNBZE7L43y8JnTs77USeJ7cpC5FoGgm3inl" } ] } ``` # 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": [ "Cristiano" ], "facebook_urls": [ { "url": "https://www.facebook.com/Cristiano/posts/pfbid0Dp9Wrmv1NAkFX1nSkKwLEKftjMSHbDYNBZE7L43y8JnTs77USeJ7cpC5FoGgm3inl" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("premiumscraper/facebook-post-engagement-scraper-lightweight-metrics").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": ["Cristiano"], "facebook_urls": [{ "url": "https://www.facebook.com/Cristiano/posts/pfbid0Dp9Wrmv1NAkFX1nSkKwLEKftjMSHbDYNBZE7L43y8JnTs77USeJ7cpC5FoGgm3inl" }], } # Run the Actor and wait for it to finish run = client.actor("premiumscraper/facebook-post-engagement-scraper-lightweight-metrics").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": [ "Cristiano" ], "facebook_urls": [ { "url": "https://www.facebook.com/Cristiano/posts/pfbid0Dp9Wrmv1NAkFX1nSkKwLEKftjMSHbDYNBZE7L43y8JnTs77USeJ7cpC5FoGgm3inl" } ] }' | apify call premiumscraper/facebook-post-engagement-scraper-lightweight-metrics --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=premiumscraper/facebook-post-engagement-scraper-lightweight-metrics", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Facebook Post Engagement Scraper ⚡ | Lightweight Metrics", "description": "Extract lightweight engagement metrics from Facebook posts. Output includes: total reactions, comment count, share count, video view count, per-type reaction breakdown (Like/Love/Haha/Wow/Sad/Angry), and calculated engagement rate. One row per post ✨ Facebook Post Engagement Scraper⚡", "version": "1.0", "x-build-id": "O2LUeyAsyYBLHYyA6" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/premiumscraper~facebook-post-engagement-scraper-lightweight-metrics/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-premiumscraper-facebook-post-engagement-scraper-lightweight-metrics", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/premiumscraper~facebook-post-engagement-scraper-lightweight-metrics/runs": { "post": { "operationId": "runs-sync-premiumscraper-facebook-post-engagement-scraper-lightweight-metrics", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/premiumscraper~facebook-post-engagement-scraper-lightweight-metrics/run-sync": { "post": { "operationId": "run-sync-premiumscraper-facebook-post-engagement-scraper-lightweight-metrics", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "facebook_urls" ], "properties": { "username": { "title": "Facebook Username(s)", "type": "array", "description": "Enter one or more Facebook usernames such as Cristiano or nike.", "items": { "type": "string" } }, "facebook_urls": { "title": "Facebook Post URLs", "type": "array", "description": "One or more direct Facebook post, video, photo, or share URLs.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } } } }, "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 } } } } } } } } } } ```