# Facebook Reviews Scraper (`calm_builder/facebook-reviews-scraper`) Actor Collect public Facebook page reviews and recommendations into clean, structured JSON format. Perfect for reputation monitoring, sentiment analysis, market research, and competitive intelligence. Gather review text, ratings, engagement metrics, and page metadata in bulk. - **URL**: https://apify.com/calm\_builder/facebook-reviews-scraper.md - **Developed by:** [Coder](https://apify.com/calm_builder) (community) - **Categories:** Social media, Lead generation, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $1.00 / 1,000 reviews 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 Reviews Scraper Collect public Facebook page reviews and recommendations from one or more page links into clean, structured JSON format. This actor is built for reputation management, sentiment analysis, market research, and competitive intelligence. It allows you to gather reviews from any public Facebook page without needing complex setups or browser automation. ### Features - **Multi-URL Support**: Process multiple Facebook pages in a single run. - **Detailed Review Data**: Collects review text, recommendation status (Yes/No), author details, and timestamps. - **Engagement Metrics**: Gathers reaction counts, share counts, and comment reply counts for each review. - **Top Comments**: Includes the first few comments/replies for each review to provide context. - **Page Metadata**: Every review record includes core page details (Page Name, URL, Overall Summary) for easy joining and grouping. - **Structured Output**: Results are returned in a clean format ready for JSON, CSV, or Excel. ### Why use this scraper? 1. **Reputation Monitoring**: Keep track of what customers are saying about your brand or your competitors. 2. **Sentiment Analysis**: Use the collected review text for NLP tasks and customer satisfaction tracking. 3. **Market Research**: Identify common pain points or praise in your industry by analyzing competitor reviews. 4. **Data Portability**: Easily export your Facebook review history into your own CRM or dashboard. ### How to Use 1. **Find Reviews Page Link**: Navigate to the Facebook page's reviews section and copy the URL (e.g., `https://www.facebook.com/pagename/reviews` or `https://www.facebook.com/profile.php?id=123&sk=reviews`). 2. **Set Limits**: Choose how many reviews you want to collect per link. 3. **Run the Actor**: Start the actor and wait for it to complete. 4. **Download Data**: Export your results in your preferred format from the dataset tab. ### Input | Field | Type | Description | |---|---|---| | **Facebook page links** (`startUrls`) | Array | List of direct links to Facebook reviews pages. | | **Maximum reviews per link** (`maxReviewsPerUrl`) | Integer | The limit of reviews to collect for each input link (Default: 5). | #### Example Input ```json { "startUrls": [ { "url": "https://www.facebook.com/USPizza.in/reviews" }, { "url": "https://www.facebook.com/copperkettleyqr/reviews" } ], "maxReviewsPerUrl": 10 } ```` ### Output Data Structure Each item in the dataset represents a single review. Below is an example of the fields you will receive: ```json { "postId": "347454313853838", "authorName": "Sãñjû Bâbã", "authorProfileUrl": "https://www.facebook.com/people/S%C3%A3%C3%B1j%C3%BB-B%C3%A2b%C3%A3/pfbid0Dh...", "authorProfileImageUrl": "https://scontent.fna.fbcdn.net/...", "text": "welcome US Pizza Modasa thank you", "isRecommended": true, "createdAt": "2022-02-09T21:06:36Z", "timestamp": 1644440796, "url": "https://www.facebook.com/permalink.php?story_fbid=pfbid0Ju...", "privacy": "Public", "reactionCount": 2, "shareCount": 0, "commentRepliesCount": 2, "topComments": [ { "authorName": "US Pizza Official", "text": "That looks delicious 😋", "createdAt": "2022-03-08T11:29:54Z" } ], "page": { "id": "100064843086340", "name": "US Pizza Official", "profileBusinessId": "69598700664", "reviewsSummary": "70% recommend (8,199 reviews)", "profileUrl": "https://www.facebook.com/USPizza.in" } } ``` ### Responsible Use Use this actor only for publicly available content and ensure your use complies with applicable laws, regulations, and platform terms. # Actor input Schema ## `startUrls` (type: `array`): Add one or more direct links to the Facebook reviews page. Examples: `https://www.facebook.com/pagename/reviews` or `https://www.facebook.com/profile.php?id=123&sk=reviews`. ## `maxReviewsPerUrl` (type: `integer`): Maximum number of reviews to collect for each input link. ## Actor input object example ```json { "startUrls": [ { "url": "https://www.facebook.com/copperkettleyqr/reviews" }, { "url": "https://www.facebook.com/USPizza.in/reviews" } ], "maxReviewsPerUrl": 5 } ``` # 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 = { "startUrls": [ { "url": "https://www.facebook.com/copperkettleyqr/reviews" }, { "url": "https://www.facebook.com/USPizza.in/reviews" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("calm_builder/facebook-reviews-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.facebook.com/copperkettleyqr/reviews" }, { "url": "https://www.facebook.com/USPizza.in/reviews" }, ] } # Run the Actor and wait for it to finish run = client.actor("calm_builder/facebook-reviews-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.facebook.com/copperkettleyqr/reviews" }, { "url": "https://www.facebook.com/USPizza.in/reviews" } ] }' | apify call calm_builder/facebook-reviews-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=calm_builder/facebook-reviews-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Facebook Reviews Scraper", "description": "Collect public Facebook page reviews and recommendations into clean, structured JSON format. Perfect for reputation monitoring, sentiment analysis, market research, and competitive intelligence. Gather review text, ratings, engagement metrics, and page metadata in bulk.", "version": "0.0", "x-build-id": "eY6gFw73WUCSgjrCB" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/calm_builder~facebook-reviews-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-calm_builder-facebook-reviews-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/calm_builder~facebook-reviews-scraper/runs": { "post": { "operationId": "runs-sync-calm_builder-facebook-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/calm_builder~facebook-reviews-scraper/run-sync": { "post": { "operationId": "run-sync-calm_builder-facebook-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "startUrls", "maxReviewsPerUrl" ], "properties": { "startUrls": { "title": "Facebook page links", "minItems": 1, "type": "array", "description": "Add one or more direct links to the Facebook reviews page. Examples: `https://www.facebook.com/pagename/reviews` or `https://www.facebook.com/profile.php?id=123&sk=reviews`.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "maxReviewsPerUrl": { "title": "Maximum reviews per link", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum number of reviews to collect for each input link.", "default": 5 } } }, "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 } } } } } } } } } } ```