# Airbnb Reviews Scraper & Sentiment Analyzer (`integrative_tangent/airbnb-reviews-sentiment`) Actor Scrape all reviews from any Airbnb listing worldwide. Includes built-in sentiment analysis (positive/negative/neutral/mixed), topic detection (cleanliness, location, value, etc.), and reviewer details. No external API costs. - **URL**: https://apify.com/integrative\_tangent/airbnb-reviews-sentiment.md - **Developed by:** [Luis Segura](https://apify.com/integrative_tangent) (community) - **Categories:** Travel, Real estate, Lead generation - **Stats:** 1 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 ## Airbnb Reviews Scraper & Sentiment Analyzer Scrape guest reviews from any Airbnb listing worldwide and get **instant sentiment analysis** with every review. No external API costs, no ChatGPT fees — sentiment scoring and topic detection are built-in. ### What does this Actor do? This Actor extracts all guest reviews from one or more Airbnb listings and enriches each review with: - **Sentiment score** (-5 to +5) — how positive or negative the review is - **Sentiment label** — `positive`, `negative`, `neutral`, or `mixed` - **Topic detection** — automatically tags what the review is about: cleanliness, location, value, amenities, communication, check-in, comfort, accuracy Works for any listing in any country. Supports reviews in English, Spanish, French, Portuguese, German, and Italian. ### Why use this instead of other review scrapers? | Feature | This Actor | Others | |---|---|---| | Sentiment analysis | Built-in (free) | Requires GPT-4 ($$$) or manual work | | Topic detection | 8 categories, multilingual | None or basic | | Cost per review | ~$0.001 | $0.01-0.05 with AI APIs | | Languages | 6 languages | English only | | Host responses | Included | Often missing | ### Use cases - **Property managers** — Monitor guest satisfaction across your portfolio. Detect negative trends (cleanliness, communication) before they hurt your ratings. - **Real estate investors** — Analyze reviews to assess listing quality before purchasing a short-term rental property. - **Market researchers** — Compare sentiment across neighborhoods, cities, or property types. Find underserved markets. - **Competitor analysis** — Benchmark your reviews against competitors. See what guests praise or complain about. - **Dynamic pricing** — Correlate sentiment trends with pricing and occupancy data. - **Travel agencies** — Curate listings with consistently positive reviews for your clients. ### Input Provide one or more Airbnb listing URLs or IDs: ```json { "listingUrls": [ "https://www.airbnb.com/rooms/23137877", "https://www.airbnb.com/rooms/45678901", "12345678" ], "maxReviewsPerListing": 100, "includeHostResponse": true, "sortBy": "MOST_RECENT" } ```` #### Input parameters | Parameter | Type | Default | Description | |---|---|---|---| | `listingUrls` | Array | Required | Airbnb listing URLs or numeric IDs | | `maxReviewsPerListing` | Number | 100 | Max reviews per listing (0 = all) | | `includeHostResponse` | Boolean | true | Include host reply to each review | | `sortBy` | String | MOST\_RECENT | Sort order: MOST\_RECENT or MOST\_RELEVANT | | `language` | String | (all) | Filter by language code (en, es, fr, etc.) | | `requestsPerSecond` | Number | 1.5 | Rate limit (lower = safer) | ### Output Each review is returned as a JSON object in the Apify Dataset: ```json { "listingId": "23137877", "listingUrl": "https://www.airbnb.com/rooms/23137877", "reviewId": "1234567890", "reviewerName": "Maria", "reviewerId": "98765432", "date": "2025-12-15", "comments": "Amazing place! The pool was spotless and the host was incredibly responsive. A bit overpriced for the area but the location makes up for it.", "rating": 5, "language": "en", "hostResponse": "Thank you Maria! We're glad you enjoyed your stay.", "hostResponseDate": "2025-12-16", "sentimentScore": 2.35, "sentimentLabel": "positive", "sentimentTopics": ["cleanliness", "communication", "value", "location"], "scrapedAt": "2026-04-05T14:30:00.000Z" } ``` #### Output fields | Field | Description | |---|---| | `sentimentScore` | Normalized score from -5 (very negative) to +5 (very positive) | | `sentimentLabel` | Overall classification: `positive`, `negative`, `neutral`, or `mixed` | | `sentimentTopics` | What the review discusses: cleanliness, location, value, amenities, communication, checkin, comfort, accuracy | | `rating` | Star rating given by the guest (1-5) | | `comments` | Full review text | | `hostResponse` | Host's reply (if enabled and available) | ### Sentiment analysis details The sentiment engine uses [AFINN](https://github.com/fnielsen/afinn) lexicon-based analysis with a custom Airbnb-specific dictionary (58 extra terms like "superhost", "cockroach", "breathtaking", etc.). **How scoring works:** - Each word in the review is scored against the lexicon - The score is normalized by review length to produce a -5 to +5 comparative score - Reviews with strong positive AND negative words are classified as "mixed" **Topic detection** scans for category-specific keywords in 6 languages, covering 8 Airbnb-relevant categories. This approach has two key advantages over LLM-based analysis: 1. **Zero latency** — analysis runs instantly, no API calls 2. **Zero cost** — no per-token charges from OpenAI or similar ### How much does it cost? The Actor uses **pay-per-event** pricing. You are charged per review scraped. Platform costs (compute, proxy, storage) are included. Typical cost: **~$1-3 per 1,000 reviews** depending on listing complexity and rate limiting. ### Tips for best results - Start with `maxReviewsPerListing: 50` to test, then increase - For listings with 1,000+ reviews, set `requestsPerSecond: 1` to avoid rate limiting - Export data as CSV or Excel from the Apify Dataset for further analysis - Use the `language` filter if you only need reviews in one language - Combine with calendar/pricing data for complete market intelligence ### Integrations Export your data to Google Sheets, Slack, Zapier, or any webhook using [Apify integrations](https://docs.apify.com/platform/integrations). Common workflows: - **Google Sheets** — Auto-update a spreadsheet with new reviews weekly - **Slack alerts** — Get notified when a competitor receives negative reviews - **Zapier/Make** — Trigger workflows based on sentiment changes ### Changelog #### v1.0.0 (2026-04-05) - Initial release - Sentiment analysis with AFINN + custom Airbnb lexicon - Topic detection across 8 categories in 6 languages - Adaptive rate limiting with automatic session refresh - Pay-per-event pricing # Actor input Schema ## `listingUrls` (type: `array`): Airbnb listing URLs to scrape reviews from. Supports full URLs (https://www.airbnb.com/rooms/12345) or just listing IDs (12345). ## `maxReviewsPerListing` (type: `integer`): Maximum number of reviews to fetch per listing. Set to 0 for all reviews (may take longer for popular listings with 500+ reviews). ## `includeHostResponse` (type: `boolean`): Include the host's response to each review (if available). ## `sortBy` (type: `string`): How to sort the reviews from Airbnb. ## `language` (type: `string`): Only fetch reviews in a specific language (ISO code, e.g. 'en', 'es', 'fr'). Leave empty for all languages. ## `proxyConfiguration` (type: `object`): Optionally use Apify proxies to avoid rate limiting. ## `requestsPerSecond` (type: `number`): Maximum requests per second. Lower values reduce chance of blocking. Recommended: 1-2. ## Actor input object example ```json { "listingUrls": [ "https://www.airbnb.com/rooms/23137877" ], "maxReviewsPerListing": 100, "includeHostResponse": true, "sortBy": "MOST_RECENT", "language": "", "requestsPerSecond": 1.5 } ``` # 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 = { "listingUrls": [ "https://www.airbnb.com/rooms/23137877" ] }; // Run the Actor and wait for it to finish const run = await client.actor("integrative_tangent/airbnb-reviews-sentiment").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 = { "listingUrls": ["https://www.airbnb.com/rooms/23137877"] } # Run the Actor and wait for it to finish run = client.actor("integrative_tangent/airbnb-reviews-sentiment").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 '{ "listingUrls": [ "https://www.airbnb.com/rooms/23137877" ] }' | apify call integrative_tangent/airbnb-reviews-sentiment --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=integrative_tangent/airbnb-reviews-sentiment", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Airbnb Reviews Scraper & Sentiment Analyzer", "description": "Scrape all reviews from any Airbnb listing worldwide. Includes built-in sentiment analysis (positive/negative/neutral/mixed), topic detection (cleanliness, location, value, etc.), and reviewer details. No external API costs.", "version": "1.0", "x-build-id": "k9jrASia72KDA2iVx" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/integrative_tangent~airbnb-reviews-sentiment/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-integrative_tangent-airbnb-reviews-sentiment", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/integrative_tangent~airbnb-reviews-sentiment/runs": { "post": { "operationId": "runs-sync-integrative_tangent-airbnb-reviews-sentiment", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/integrative_tangent~airbnb-reviews-sentiment/run-sync": { "post": { "operationId": "run-sync-integrative_tangent-airbnb-reviews-sentiment", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "listingUrls" ], "properties": { "listingUrls": { "title": "Listing URLs", "type": "array", "description": "Airbnb listing URLs to scrape reviews from. Supports full URLs (https://www.airbnb.com/rooms/12345) or just listing IDs (12345).", "items": { "type": "string" } }, "maxReviewsPerListing": { "title": "Max reviews per listing", "minimum": 0, "maximum": 5000, "type": "integer", "description": "Maximum number of reviews to fetch per listing. Set to 0 for all reviews (may take longer for popular listings with 500+ reviews).", "default": 100 }, "includeHostResponse": { "title": "Include host responses", "type": "boolean", "description": "Include the host's response to each review (if available).", "default": true }, "sortBy": { "title": "Sort reviews by", "enum": [ "MOST_RECENT", "MOST_RELEVANT" ], "type": "string", "description": "How to sort the reviews from Airbnb.", "default": "MOST_RECENT" }, "language": { "title": "Language filter", "type": "string", "description": "Only fetch reviews in a specific language (ISO code, e.g. 'en', 'es', 'fr'). Leave empty for all languages.", "default": "" }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Optionally use Apify proxies to avoid rate limiting." }, "requestsPerSecond": { "title": "Requests per second", "minimum": 0.3, "maximum": 5, "type": "number", "description": "Maximum requests per second. Lower values reduce chance of blocking. Recommended: 1-2.", "default": 1.5 } } }, "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 } } } } } } } } } } ```