# Facebook Comments Scraper (`scraper_one/facebook-comments-scraper`) Actor Extract comments from Facebook posts provided as input URLs. Retrieve comment text, authors, timestamps, reactions, and more. Ideal for social media monitoring, sentiment analysis, and engagement tracking. 🚀 - **URL**: https://apify.com/scraper\_one/facebook-comments-scraper.md - **Developed by:** [Scraper One](https://apify.com/scraper_one) (community) - **Categories:** Social media, Automation, Developer tools - **Stats:** 535 total users, 43 monthly users, 100.0% runs succeeded, 15 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing from $0.40 / 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. 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 Comments Scraper ![Apify Actor](https://img.shields.io/badge/Apify-Actor-blue) This **Apify Actor** extracts comments from **Facebook posts** provided as input URLs. It retrieves comment text, authors, timestamps, reactions, and more. This tool is ideal for **social media monitoring, sentiment analysis, and engagement tracking**. 🚀 --------------- ### Features - 🔍 Scrape **comments from multiple posts** - 👥 Extract **author details and profile URLs** - 📅 Retrieve **timestamps and reactions** - 🔢 Limit the number of comments per post ### Input Parameters | Parameter | Type | Required | Description | |--------------------|------------|----------|----------------------------------------------------------------------------------------------------------------------------------------------------| | `postUrls` | `string[]` | ✅ | Array of Facebook post URLs to extract comments from. | | `resultsLimit` | `number` | ❌ | Maximum number of comments per post (optional). If not set, only a few of the first replies will be returned. | | `commentsSortType` | `string` | ❌ | Type of comments (sorting) to fetch: `"relevant"` (most relevant), `"newest"` or `"all"`. Defaults to `"relevant` if not set (Facebook's default). | ### Example Input ```json { "postUrls": [ "https://www.facebook.com/fanpage.TECHART/posts/pfbid0ZYMHCBMGHHQ9W98d9goZ4VpxTeLJSxsZGLfa2V2qbdH6jUyLEUubNTtU7joTi2vVl" ], "resultsLimit": 50 } ```` ### Output Data The actor returns an array of JSON objects with extracted comments data. #### Example Output ```json [ { "commentText": "George Kittle must've had a word with the GM", "id": "Y29tbWVudDoxMTg2ODEyNDY5NDgyMjc1XzY2ODE2MzY0NTU0NjI3Mg==", "legacyId": 668163645546272, "timestamp": 1742045152000, "url": "https://www.facebook.com/NFL/posts/pfbid023uiL1TJbp9QxWuCXSR3JamtrXev9LGDNHnpQAuf1dr6kU7Em8hU3oLms5mb4KZQhl?comment_id=668163645546272", "author": { "id": "pfbid027qk7JdC2FUy2SHN9PQ1uQrPUAwaSaKVCTNFD6KeN9GRfdw7n4C5k3w6naCtYseQZl", "profilePictureUrl": "https://scontent.fpoz3-1.fna.fbcdn.net/v/t39.30808-1/484832087_2619507948255427_8811130316462776878_n.jpg?stp=cp6_dst-jpg_s50x50_tt6&_nc_cat=107&ccb=1-7&_nc_sid=e99d92&_nc_ohc=8WugMfDPwGAQ7kNvgFARVYa&_nc_oc=Adk98TB_DjhE7FBLYrhYQSa1s9-iOs0bcnRyTpUO3H0SMbziMMFJu-GYw9xqkuy1ZFE&_nc_zt=24&_nc_ht=scontent.fpoz3-1.fna&_nc_gid=bRJ5zIIdp6dC4pjPIysFaA&oh=00_AYEDOB5Oa9JFPYnAZ2uN6tk-WjfJ34PmbS1pY4e13oWLbw&oe=67E0EC7E", "name": "Zack Crouch" }, "postUrl": "https://www.facebook.com/NFL/posts/pfbid037dWXDmChUtBRycRAoowDn6oSsv5Qjnr5ZC4tbAYGTtPeJuWGS27JgqsdpjdR1Hwzl", "reactions": { "like": 178, "love": 8, "haha": 4, "support": 1 }, "reactionsCount": "191" } ] ``` ###### Let me know if you need additional output fields! 🤙 ### Usage 1. **Create an Apify account** and navigate to the actor. 2. **Configure input parameters** in the Apify UI or via API. 3. **Run the actor** and monitor execution logs. 4. **Download extracted comments** as JSON, CSV, or Excel. ### Limitations & Notes - Scraping Facebook data **must comply with their Terms of Service**. - Avoid excessive scraping to prevent IP bans. - The accuracy of data depends on Facebook’s page structure and visibility settings. - Rate-limited – Free users can make only a few requests per day. **Contact us if you need higher or custom limits!** *** ### Works Best With For the best results, use this scraper alongside [Facebook Posts Search](https://apify.com/scraper_one/facebook-posts-search). Before extracting comments, you can use the Facebook Posts Search actor to gather post URLs based on specific keywords. Then, pass those URLs into this Facebook Comments Scraper to collect comments associated with those posts. ✅ Best Use Case Scenario - Run Facebook Posts Search Scraper → Collect posts based on your search criteria. - Feed post URLs into Facebook Comments Scraper → Extract comments for each post. - Gain complete insights → Combine posts and comments for a full dataset, useful for engagement analysis, sentiment tracking, and social media monitoring. This combination provides a powerful way to analyze conversations happening around specific posts! 🚀 ### Other Recommended Scrapers If you're working with multiple platforms or want additional data sources, check out these scrapers: - 🐦 [X (Twitter) Posts Search](https://apify.com/scraper_one/x-posts-search) — Find posts/tweets based on keywords, hashtags, and more - 🐦 [X (Twitter) Post Replies Scraper](https://apify.com/scraper_one/x-post-replies-scraper) — Scrap replies of multiple X (Twitter) posts - 🐦 [X (Twitter) Profile Posts Scraper](https://apify.com/scraper_one/x-profile-posts-scraper) — Scrap posts by specified X profiles/users - 📘 [Facebook Posts Search](https://apify.com/scraper_one/facebook-posts-search) — Discover Facebook posts for a given topic or page - 📘 [Facebook Comments Scraper](https://apify.com/scraper_one/facebook-comments-scraper) — Extract comments from public Facebook posts - 📘 [Facebook Reactions Scraper](https://apify.com/scraper_one/facebook-reactions-scraper) — Scrap reactions from Facebook posts (like, sad, haha, angry etc.) - 📘 [Facebook Posts Scraper](https://apify.com/scraper_one/facebook-posts-scraper) — Scrap posts from Facebook pages, groups etc. - 💬 [YouTube Search Scraper](https://apify.com/scraper_one/youtube-search-scraper) — Extract search results from YouTube - 💬 [YouTube Comments Scraper](https://apify.com/scraper_one/youtube-comments-scraper) — Extract comments from YouTube videos - 🎬 [YouTube Downloader](https://apify.com/scraper_one/yt-downloader) — Download youtube videos ### Support & Contact ✉️ If you encounter issues or need help, feel free to **open an issue** or contact us at **scraper1one@gmail.com**. # Actor input Schema ## `postUrls` (type: `array`): List of post URLs to process ## `resultsLimit` (type: `integer`): Maximum number of replies to retrieve per post (between 1 and 500). If not set, only a few of the first replies will be returned. ## `commentsSortType` (type: `string`): Comments sorting - i.e. what kind of comments to scrape for. If not set, platform default will be used ('Most relevant'). Note: Choosing 'All comments' still requires setting a 'Results Limit'. ## Actor input object example ```json { "postUrls": [ "https://www.facebook.com/NFL/posts/pfbid037dWXDmChUtBRycRAoowDn6oSsv5Qjnr5ZC4tbAYGTtPeJuWGS27JgqsdpjdR1Hwzl", "https://www.facebook.com/oldmillartsOMA/posts/pfbid02gEbMLP6JZfCfyjh62nC7VkxYhtzp1heiTTnrAW57qNnZZ7r2Z31Ponn6tfPooRJyl" ], "resultsLimit": 20 } ``` # 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 = { "postUrls": [ "https://www.facebook.com/NFL/posts/pfbid037dWXDmChUtBRycRAoowDn6oSsv5Qjnr5ZC4tbAYGTtPeJuWGS27JgqsdpjdR1Hwzl", "https://www.facebook.com/oldmillartsOMA/posts/pfbid02gEbMLP6JZfCfyjh62nC7VkxYhtzp1heiTTnrAW57qNnZZ7r2Z31Ponn6tfPooRJyl" ], "resultsLimit": 20 }; // Run the Actor and wait for it to finish const run = await client.actor("scraper_one/facebook-comments-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 = { "postUrls": [ "https://www.facebook.com/NFL/posts/pfbid037dWXDmChUtBRycRAoowDn6oSsv5Qjnr5ZC4tbAYGTtPeJuWGS27JgqsdpjdR1Hwzl", "https://www.facebook.com/oldmillartsOMA/posts/pfbid02gEbMLP6JZfCfyjh62nC7VkxYhtzp1heiTTnrAW57qNnZZ7r2Z31Ponn6tfPooRJyl", ], "resultsLimit": 20, } # Run the Actor and wait for it to finish run = client.actor("scraper_one/facebook-comments-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 '{ "postUrls": [ "https://www.facebook.com/NFL/posts/pfbid037dWXDmChUtBRycRAoowDn6oSsv5Qjnr5ZC4tbAYGTtPeJuWGS27JgqsdpjdR1Hwzl", "https://www.facebook.com/oldmillartsOMA/posts/pfbid02gEbMLP6JZfCfyjh62nC7VkxYhtzp1heiTTnrAW57qNnZZ7r2Z31Ponn6tfPooRJyl" ], "resultsLimit": 20 }' | apify call scraper_one/facebook-comments-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scraper_one/facebook-comments-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Facebook Comments Scraper", "description": "Extract comments from Facebook posts provided as input URLs. Retrieve comment text, authors, timestamps, reactions, and more. Ideal for social media monitoring, sentiment analysis, and engagement tracking. 🚀", "version": "0.0", "x-build-id": "2D9LZ1Zp6j8TtjwP1" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scraper_one~facebook-comments-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scraper_one-facebook-comments-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scraper_one~facebook-comments-scraper/runs": { "post": { "operationId": "runs-sync-scraper_one-facebook-comments-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scraper_one~facebook-comments-scraper/run-sync": { "post": { "operationId": "run-sync-scraper_one-facebook-comments-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "postUrls" ], "properties": { "postUrls": { "title": "Post URLs", "maxItems": 5, "type": "array", "description": "List of post URLs to process", "items": { "type": "string" } }, "resultsLimit": { "title": "Results Limit", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum number of replies to retrieve per post (between 1 and 500). If not set, only a few of the first replies will be returned." }, "commentsSortType": { "title": "Comments Sort Type", "enum": [ "relevant", "newest", "all" ], "type": "string", "description": "Comments sorting - i.e. what kind of comments to scrape for. If not set, platform default will be used ('Most relevant'). Note: Choosing 'All comments' still requires setting a 'Results Limit'." } } }, "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 } } } } } } } } } } ```