# Facebook Posts Scraper (`scrapers-hub/facebook-posts-scraper`) Actor πŸ“Œ Facebook Posts Scraper extracts public posts fastβ€”capturing post text, links, dates, reactions & more. πŸš€ Perfect for social media research, brand monitoring, competitor insights & lead discovery. ⚑ Get structured data in minutes! - **URL**: https://apify.com/scrapers-hub/facebook-posts-scraper.md - **Developed by:** [Scrapers Hub](https://apify.com/scrapers-hub) (community) - **Categories:** Social media, Lead generation, Automation - **Stats:** 3 total users, 2 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $2.99 / 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. 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 ### πŸš€ Facebook Posts Scraper: The Definitive Enterprise Guide for Social Content Automation In the high-stakes world of digital intelligence, the ability to transform raw social media activity into structured, analytical data is a superpower. The Facebook Posts Scraper is a professional-grade, high-performance automation engine meticulously engineered to harvest public posts, engagement signals, and media assets at scale. By leveraging the Facebook Posts Scraper, organizations can move beyond manual observation and enter the realm of big data analytics, converting thousands of status updates into a centralized repository of market intelligence. πŸ“ˆ Whether your objective is to track the digital narrative of a world-class athlete, audit the content strategy of a multinational brand, or monitor local market trends, the Facebook Posts Scraper serves as your primary data pipeline. This documentation provides an exhaustive exploration of the architecture, strategic methodologies, and technical superiorities of the Facebook Posts Scraper in the current 2026 digital ecosystem. 🌐 #### πŸ—οΈ 1. Technical Architecture of the Facebook Posts Scraper The Facebook Posts Scraper is built upon a resilient, headless-browser framework designed to overcome the challenges of modern, single-page applications (SPA). Facebook's interface is notoriously dynamic, utilizing complex JavaScript and "infinite scroll" mechanisms. The Facebook Posts Scraper is specifically tuned to navigate these hurdles, ensuring that data is extracted only after the content is fully rendered and stabilized within the Document Object Model (DOM). #### βš™οΈ Automation Configuration (Input Parameter Guide) 🎨 Target Flexibility – Simply provide a direct link, and the Facebook Posts Scraper will automatically identify if it is dealing with a Page or a Profile. πŸ”’ Depth Control – Use the max_pages parameter to define the scrolling limit. The Facebook Posts Scraper can navigate hundreds of scrolls to reach historical data. πŸ•’ Wait-State Management – The Facebook Posts Scraper includes intelligent "jitter" delays to mimic human behavior and ensure all lazy-loaded images are captured. πŸ”— Universal Compatibility – The Facebook Posts Scraper handles all Facebook subdomains (web.facebook.com, m.facebook.com, etc.) without requiring manual conversion. #### πŸ“₯ Input Specification Configure your scraping task using the following JSON structure: ```json { "target_url": "https://www.facebook.com/leomessi", "max_pages": 1000 } ```` ###### target\_url: The full link to the Facebook profile or business page. ###### max\_pages: The limit for page scrolling/depth to determine how many posts are retrieved. #### πŸ“€ Output Structure & Schema The scraper returns a clean, structured object for every post found: ```json { "name": "Leo Messi", "profile_pic": "https://z-p3-scontent.fdac3-2.fna.fbcdn.net/v/t1.6435-1/...", "message": "Aunque pudimos haber ganado ayer, la verdad es que logramos una clasificaciΓ³n...", "story_id": "1355105292647724", "story_url": null, "actor_url": "https://www.facebook.com/leomessi", "attachment_url": "https://www.facebook.com/leomessi/posts/pfbid0Nj7...", "creation_time": 1750794906, "readable_time": "2025-06-25 01:55:06", "user_id": "100044447978953" } ``` #### πŸ›  Pro-Tips for Advanced Filtering To get the most out of your results, follow these strategies after exporting: Filter by Media: Sort the attachment\_url column to identify posts that contain visual media versus plain text. Keyword Extraction: Use Excel or Python to search the message field for specific product names or promotional terms (e.g., "Sale", "New Launch"). Chronological Mapping: Sort by creation\_time (Ascending) to see the evolution of a brand's narrative from its very first post. #### 🌟 2. Key Features of the Facebook Posts Scraper The Facebook Posts Scraper stands out in the industry due to its unique combination of speed, stealth, and data depth. Below are the core pillars that define the Facebook Posts Scraper: πŸ”’ Zero-Authentication Extraction – The Facebook Posts Scraper operates entirely on public-facing data. No login credentials or session cookies are required, protecting your own accounts from risk. πŸ“„ Dual-Entity Intelligence – Whether the target is a verified business Page or a public personal Profile, the Facebook Posts Scraper adapts its logic automatically. 🏒 Massive Historical Reach – Capable of retrieving up to 5,000+ posts per target (depending on page depth), making the Facebook Posts Scraper ideal for archiving. πŸ–ΌοΈ Rich Metadata Harvest – Captures full text (with emojis), Story IDs, actor URLs, and direct high-resolution attachment links. ⚑ Smart Pagination Engine – The Facebook Posts Scraper triggers "Load More" actions with precision, avoiding the traps of infinite scroll loops. πŸ“Š Time-Series Ready – Every result from the Facebook Posts Scraper includes both Unix and human-readable timestamps for instant chronological sorting. #### πŸ›‘οΈ 3. The "No-Login" Security Protocol of the Facebook Posts Scraper Security and account longevity are critical for data scientists. The Facebook Posts Scraper is engineered to be non-intrusive. πŸ‘€ Anonymous Guest Footprint – The Facebook Posts Scraper interacts with the platform as an anonymous guest, leaving no digital trail back to your organization. 🚫 Bypassing Account Blocks – By staying logged out, the Facebook Posts Scraper avoids the "checkpoints" and "suspicious activity" flags that plague traditional scrapers. πŸ›‘οΈ Anti-Fingerprinting Stealth – The Facebook Posts Scraper rotates user-agents and browser headers, mimicking different devices (iOS, Android, Windows) to stay under the radar. 🌍 Global Proxy Integration – Pair the Facebook Posts Scraper with residential proxies to see localized content from any country on earth. #### πŸ“Š 4. Data Extraction Capabilities (Schema Mapping) The Facebook Posts Scraper delivers a comprehensive dataset for every post found. Below is the mapping of data fields provided by the Facebook Posts Scraper: | Data Field | Type | Insight Gained from Facebook Posts Scraper | | -------------- | ------- | ------------------------------------------------------------------- | | name | String | Confirms the entity (user or page) posting the content. | | message | Text | Full text used for NLP, keyword extraction, and sentiment analysis. | | story\_id | String | Unique database key for post tracking and de-duplication. | | attachment\_url | URL | Direct link to photos, videos, or external shared articles. | | creation\_time | Integer | Unix timestamp enabling mathematical time-series analysis. | | readable\_time | Date | Human-friendly timestamp (YYYY-MM-DD HH:MM:SS). | | user\_id | ID | Permanent numerical identifier of the actor or page. | #### πŸ“ˆ 5. Strategic Industry Use Cases for the Facebook Posts Scraper How are elite organizations utilizing the Facebook Posts Scraper to outperform their competition? 🎯 Content Strategy Optimization – Use the Facebook Posts Scraper to identify which types of media (video vs. image) your competitors post most frequently. πŸ“Š Sentiment & Crisis Monitoring – Feed the message field from the Facebook Posts Scraper into a sentiment analysis engine to detect public PR crises early. πŸš€ Viral Trend Discovery – Analyze high-engagement posts extracted by the Facebook Posts Scraper to understand what topics are currently trending in your niche. πŸ“‰ Keyword Density Mapping – Use the Facebook Posts Scraper to see how often a competitor mentions specific product names or hashtags. 🏒 Archival & Compliance – Financial institutions use the Facebook Posts Scraper to maintain a permanent record of public announcements for legal compliance. πŸ•΅οΈβ€β™‚οΈ Influencer Vetting – Use the Facebook Posts Scraper to audit years of a public figure's history to ensure their past messaging aligns with current brand values. #### πŸ› οΈ 6. Advanced Technical Workflows with the Facebook Posts Scraper The Facebook Posts Scraper is a modular component that fits into any modern data stack. πŸ”„ Real-Time Data Pipelines – Trigger the Facebook Posts Scraper via a Cron job every hour to keep your internal database synchronized with the latest social updates. πŸ€– AI-Driven Personalization – Feed the text extracted by the Facebook Posts Scraper into an LLM (Large Language Model) to generate automated summaries or creative responses. πŸ“Š Engagement Correlation – Combine Facebook Posts Scraper data with stock market prices or sales figures to see if social media activity correlates with financial performance. #### 🧠 7. Unique Intelligence & Growth Strategies Beyond basic scraping, the Facebook Posts Scraper allows for advanced behavioral observation: Posting Velocity Analysis: By using the readable\_time from the Facebook Posts Scraper, you can determine the exact hours of the day when a global brand is most active across different time zones. Semantic Evolution Tracking: Run the Facebook Posts Scraper on a 5-year history of a brand. Use the data to visualize how their messaging has shifted from "Product-Centric" to "Experience-Centric." Media Repository Generation: Automate the collection of every attachment\_url from the Facebook Posts Scraper to build a comprehensive visual mood board of your industry's advertising. #### πŸ›‘οΈ 8. Advanced Anti-Detection & Scalability The Facebook Posts Scraper is engineered for high-volume enterprise operations. 🎭 Browser Identity Blending – The Facebook Posts Scraper constantly rotates its "hardware footprint," making it indistinguishable from thousands of different legitimate users. 🌍 Proxy Diversification – The Facebook Posts Scraper supports rotating residential proxy pools, ensuring a 100% success rate even when processing thousands of pages. ⏳ Adaptive Load Balancing – To protect the integrity of the source platform, the Facebook Posts Scraper automatically slows down or speeds up based on the server response time. #### ❓ 9. Frequently Asked Questions (FAQ) 🏒 Can the Facebook Posts Scraper see posts from private groups? No. The Facebook Posts Scraper is strictly for public data. If a logged-out guest cannot see it, the Facebook Posts Scraper will not extract it. πŸ”’ πŸ“… How far back can the Facebook Posts Scraper go? As long as the posts are visible on the page, the Facebook Posts Scraper can retrieve them. You just need to increase the max\_pages limit. ⏳ ♾️ Why are some URLs null? Due to internal platform shifts, the Facebook Posts Scraper prioritizes the attachment\_url and story\_id, which are the most reliable links for data analysis. βœ… πŸ“‚ What output formats does it support? The Facebook Posts Scraper exports to JSON, CSV, Excel, and XML. #### πŸ›‘οΈ 10. Ethical Standards and Legal Compliance Using the Facebook Posts Scraper comes with a commitment to responsible data usage. βš–οΈ πŸ›οΈ Respecting the Public Web – The Facebook Posts Scraper only extracts data that users have intentionally shared with the general public. 🚦 Rate Limit Compliance – The Facebook Posts Scraper is designed to be a "considerate visitor," utilizing delays to avoid server strain. βš–οΈ Data Privacy – The Facebook Posts Scraper focuses on content and metadata; it does not harvest private emails, phone numbers, or hidden personal contacts. 🀝 Transparency – We advocate for the use of the Facebook Posts Scraper for market research and competitive transparency within the boundaries of local laws (GDPR/CCPA). #### πŸ“Š 11. Data Enrichment API Mapping Table For developers looking to integrate the Facebook Posts Scraper with third-party tools: | Feature | Enrichment Source | Purpose with Facebook Posts Scraper | | --------------------- | ------------------------- | ------------------------------------------------------------------------------------------------------- | | Sentiment Analysis | Google Vertex AI / OpenAI | Automatically analyze and score the sentiment of the `message` extracted by the Facebook Posts Scraper. | | Identity Verification | Official Company Registry | Cross-reference the `user_id` from the Facebook Posts Scraper with registered business records. | | Image Recognition | Amazon Rekognition | Detect objects, logos, or scenes within the `attachment_url` collected by the Facebook Posts Scraper. | | CRM Ingestion | HubSpot / Salesforce | Populate CRM systems with competitor updates and fresh content from the Facebook Posts Scraper. | #### 🏁 12. Conclusion: Master the Social Narrative In the data-driven landscape of 2026, those who can observe their environment most accurately win. The Facebook Posts Scraper is the ultimate bridge between unstructured social noise and clear, strategic business intelligence. It eliminates the manual work of monitoring and replaces it with a streamlined, automated data pipeline. 🌟 Whether you are a startup looking for your first market insights, an agency building a multi-brand audit, or a researcher tracking the history of public discourse, the Facebook Posts Scraper is your most reliable partner. By choosing the Facebook Posts Scraper, you are investing in a scalable intelligence strategy that will serve your organization for years to come. πŸš€πŸ“ˆ #### πŸš€ Get Started with the Facebook Posts Scraper Today! Are you ready to revolutionize your social media data collection? The Facebook Posts Scraper is waiting for your first target URL. If you need a custom configuration for the Facebook Posts Scraper or help setting up a cloud-based schedule, our technical team is here to support you. 🀝 # Actor input Schema ## `target_url` (type: `string`): The URL of the Facebook page or profile to scrape. ## `max_items` (type: `integer`): Enter max\_items ## `captionText` (type: `boolean`): Fetch the spoken transcript (captions) for video/reel posts. Adds an extra request per video, so it is slower. ## Actor input object example ```json { "target_url": "https://www.facebook.com/leomessi", "max_items": 10, "captionText": false } ``` # 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 = { "target_url": "https://www.facebook.com/leomessi" }; // Run the Actor and wait for it to finish const run = await client.actor("scrapers-hub/facebook-posts-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ 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); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ 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 = { "target_url": "https://www.facebook.com/leomessi" } # Run the Actor and wait for it to finish run = client.actor("scrapers-hub/facebook-posts-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "target_url": "https://www.facebook.com/leomessi" }' | apify call scrapers-hub/facebook-posts-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapers-hub/facebook-posts-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Facebook Posts Scraper", "description": "πŸ“Œ Facebook Posts Scraper extracts public posts fastβ€”capturing post text, links, dates, reactions & more. πŸš€ Perfect for social media research, brand monitoring, competitor insights & lead discovery. ⚑ Get structured data in minutes!", "version": "0.1", "x-build-id": "Gk0dGYYROWeBXltHh" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapers-hub~facebook-posts-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapers-hub-facebook-posts-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrapers-hub~facebook-posts-scraper/runs": { "post": { "operationId": "runs-sync-scrapers-hub-facebook-posts-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrapers-hub~facebook-posts-scraper/run-sync": { "post": { "operationId": "run-sync-scrapers-hub-facebook-posts-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "target_url" ], "properties": { "target_url": { "title": "Target URL", "type": "string", "description": "The URL of the Facebook page or profile to scrape." }, "max_items": { "title": "Max Items", "type": "integer", "description": "Enter max_items", "default": 10 }, "captionText": { "title": "Include video transcript", "type": "boolean", "description": "Fetch the spoken transcript (captions) for video/reel posts. Adds an extra request per video, so it is slower.", "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 } } } } } } } } } } ```