# Airbnb Reviews Scraper (`stealth_mode/airbnb-reviews-scraper`) Actor
Scrape guest reviews from any Airbnb listing — including ratings, reviewer profiles, host responses, review media, and highlights. Collect up to 200 reviews per URL with flexible sorting and offset options. Perfect for hosts, analysts, and researchers.
- **URL**: https://apify.com/stealth\_mode/airbnb-reviews-scraper.md
- **Developed by:** [Stealth mode](https://apify.com/stealth_mode) (community)
- **Categories:** Automation, Developer tools, Travel
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks
- **User rating**: No ratings yet
## Pricing
from $2.00 / 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.
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
## Airbnb Reviews Scraper: Extract Guest Reviews & Ratings at Scale
---
### What Is Airbnb.com?
Airbnb is the world's leading short-term rental marketplace, hosting millions of property listings across 220+ countries. Guest reviews are among the most valuable data points on the platform — they directly influence booking decisions, host reputation, and pricing strategies. Manually collecting this review data is impractical at scale. The **Airbnb Reviews Scraper** automates extraction, delivering structured review records ready for analysis.
---
### Overview
The **Airbnb.com Reviews Scraper** targets individual listing pages and extracts all publicly visible guest reviews, including text content, ratings, reviewer metadata, host responses, review highlights, and attached media. It supports sorting, pagination via offset, and bulk URL runs.
Designed for:
- **Hosts & property managers** monitoring guest sentiment and competitor reputation
- **Market researchers** analyzing review trends across regions or property types
- **Data scientists** building sentiment analysis or NLP datasets from real hospitality reviews
- **Travel platforms** aggregating review content for comparison tools
---
### Input Format
```json
{
"urls": [
"https://www.airbnb.com/rooms/12937?source_impression_id=p3_1779704219_P30eqXRfLO5jT57C&review_page_entrypoint=show_all"
],
"sort_by": "BEST_QUALITY",
"offset": 20,
"max_items_per_url": 200,
"ignore_url_failures": true
}
````
| Field | Type | Default | Description |
|---|---|---|---|
| `urls` | `array` | — | Airbnb room detail page URLs to scrape. Paste one per line or use Bulk Edit. The URL should point to a listing's room page (e.g., `/rooms/12937`). |
| `sort_by` | `string` | `BEST_QUALITY` | Sort order for reviews. Options: `BEST_QUALITY` (Relevance), `MOST_RECENT` (Date: New to Old), `RATING_DESC` (Rating: High to Low), `RATING_ASC` (Rating: Low to High). |
| `offset` | `integer` | `0` | Number of reviews to skip before starting collection. Useful for paginating large listings or resuming interrupted runs. |
| `max_items_per_url` | `integer` | `20` | Maximum reviews to collect per URL. Can be set up to `200` or more depending on listing size. |
| `ignore_url_failures` | `boolean` | `true` | If `true`, failed URLs are skipped and the run continues. Recommended for bulk jobs. |
> **Tip:** Use `offset` + `max_items_per_url` together to paginate across a listing with thousands of reviews (e.g., offset `0`, `200`, `400`…).
***
### Output Format
**Sample output**
```json
{
"collection_tag": null,
"comments": "Lovely house and so close to the subway and easy to get around. Great bathroom and fantastic shower. Orestes's was always on hand to ask questions and support us if we needed anything.
After a day of exploring it was a welcoming place to come back to. Thank you.",
"id": "1443616429473678676",
"language": "en",
"created_at": "2025-06-14T19:28:08Z",
"responder": null,
"reviewee": {
"__typename": "ReviewUser",
"deleted": false,
"first_name": "Orestes",
"host_name": "Orestes",
"id": "50124",
"contextual_user_id": "1462507638639660367",
"picture_url": "https://a0.muscache.com/im/pictures/user/ebac33aa-6e5a-4279-8a92-0968ddf66ae2.jpg",
"profile_path": "/users/profile/1462507638639660367",
"is_superhost": false,
"user_profile_picture": {
"__typename": "Image",
"base_url": "https://a0.muscache.com/im/pictures/user/ebac33aa-6e5a-4279-8a92-0968ddf66ae2.jpg",
"on_press_action": {
"__typename": "NavigateToUserProfile",
"url": "/users/profile/1462507638639660367"
}
}
},
"reviewer": {
"__typename": "ReviewUser",
"deleted": false,
"first_name": "Leanne",
"host_name": "Leanne",
"id": "180231216",
"contextual_user_id": "1474048125995756281",
"picture_url": "https://a0.muscache.com/im/pictures/user/5b20353d-2f55-42d7-ba64-76e2bb44e4ac.jpg",
"profile_path": "/users/profile/1474048125995756281",
"is_superhost": false,
"user_profile_picture": {
"__typename": "Image",
"base_url": "https://a0.muscache.com/im/pictures/user/5b20353d-2f55-42d7-ba64-76e2bb44e4ac.jpg",
"on_press_action": {
"__typename": "NavigateToUserProfile",
"url": "/users/profile/1474048125995756281"
}
}
},
"review_highlight": null,
"highlight_type": "LENGTH_OF_STAY",
"localized_date": "June 2025",
"localized_responded_date": null,
"localized_reviewer_location": "8 years on Airbnb",
"localized_review": null,
"rating": 5,
"rating_accessibility_label": "Rating, 5 stars",
"recommended_number_of_lines": null,
"response": null,
"room_type_listing_title": null,
"room_type_listing_id": null,
"highlighted_review_sentence": [],
"highlight_review_mentioned": null,
"show_more_button": {
"__typename": "BasicListItem",
"title": "Show more",
"logging_event_data": {
"__typename": "LoggingEventData",
"logging_id": "pdp.reviews.readMore",
"experiments": [],
"event_data": null,
"event_data_schema_name": null,
"section": null,
"component": null
}
},
"subtitle_items": [],
"channel": null,
"review_media_items": [],
"is_host_highlighted_review": null,
"review_photo_urls": [],
"comment_v2": "Lovely house and so close to the subway and easy to get around. Great bathroom and fantastic shower. Orestes's was always on hand to ask questions and support us if we needed anything.
After a day of exploring it was a welcoming place to come back to. Thank you.",
"localized_comment_v2": {
"__typename": "LocalizedReview",
"comments": "Lovely house and so close to the subway and easy to get around. Great bathroom and fantastic shower. Orestes's was always on hand to ask questions and support us if we needed anything.
After a day of exploring it was a welcoming place to come back to. Thank you.",
"comments_language": "en",
"disclaimer": null,
"needs_translation": false,
"response": null,
"response_disclaimer": null
},
"localized_paid_promotion_disclaimer": null,
"from_url": "https://www.airbnb.com/rooms/12937/reviews?source_impression_id=p3_1779704219_P30eqXRfLO5jT57C&review_page_entrypoint=show_all"
}
```
Each review yields a record with 30+ fields:
#### Review Content
| Field | Meaning |
|---|---|
| `ID` | Unique Airbnb identifier for this review |
| `Comments` | Raw guest review text |
| `Comment V2` | Alternative/updated version of the comment text |
| `Localized Review` | Review text localized to the scraper's target language |
| `Localized Comment V2` | Localized version of the Comment V2 field |
| `Response` | Host's written response to the review, if any |
| `Rating` | Numeric star rating given by the guest (typically 1–5) |
| `Rating Accessibility Label` | Screen-reader-friendly label for the rating (e.g., "5 out of 5 stars") |
| `Highlighted Review Sentence` | A key sentence extracted or flagged as a highlight |
| `Review Highlight` | Category or tag of the highlight (e.g., cleanliness, location) |
| `Highlight Type` | Type classification of the review highlight |
| `Highlight Review Mentioned` | Whether the highlight topic was explicitly mentioned in the text |
| `Is Host Highlighted Review` | `true` if the host has featured this review |
| `Show More Button` | Indicates if the full review requires expansion (truncated content) |
| `Recommended Number Of Lines` | Display hint for UI rendering of review length |
| `Localized Paid Promotion Disclaimer` | Disclaimer text if the review is associated with a promotion |
#### Dates & Localization
| Field | Meaning |
|---|---|
| `Created At` | ISO timestamp of when the review was submitted |
| `Localized Date` | Human-readable review date in the listing's locale (e.g., "May 2025") |
| `Localized Responded Date` | Human-readable date of the host's response |
| `Localized Reviewer Location` | Reviewer's displayed home location (e.g., "Paris, France") |
| `Language` | Language code of the review content (e.g., `en`, `fr`, `de`) |
#### People & Parties
| Field | Meaning |
|---|---|
| `Reviewer` | Guest who wrote the review — may include name, avatar, and profile metadata |
| `Reviewee` | The host or listing being reviewed |
| `Responder` | The person (usually host) who wrote the response |
#### Listing Context
| Field | Meaning |
|---|---|
| `Room Type Listing Title` | Title of the Airbnb listing the review belongs to |
| `Room Type Listing ID` | Airbnb listing ID for cross-referencing |
| `Channel` | Platform channel the booking originated from (e.g., Airbnb, partner) |
| `Collection Tag` | Internal tag grouping the review within a collection |
| `Subtitle Items` | Supplementary metadata shown under the reviewer name |
#### Media
| Field | Meaning |
|---|---|
| `Review Media Items` | Structured media objects attached to the review |
| `Review Photo URLs` | Direct URLs to guest-uploaded review photos |
***
### How to Use
1. **Get listing URLs** — Open any Airbnb listing, scroll to the reviews section, and copy the page URL (format: `airbnb.com/rooms/{ID}`).
2. **Configure input** — Paste URLs into `urls`. Set `sort_by` to your preferred order and `max_items_per_url` based on how many reviews you need.
3. **Use offset for pagination** — For listings with many reviews, run multiple jobs with incrementing `offset` values (`0`, `200`, `400`…).
4. **Run and export** — Start the scraper, then download results as JSON, CSV, or Excel.
**Best practices:**
- Set `ignore_url_failures: true` for multi-URL batch runs.
- Use `MOST_RECENT` sort to track new reviews over time with a small `max_items_per_url`.
- Cross-reference `Room Type Listing ID` when scraping multiple listings to keep data organized.
**Common issues:**
- Ensure the URL is a room detail page (`/rooms/`), not a search results page.
- Some listings may have geo-restricted visibility — use a proxy matching the listing's country if available.
***
### Use Cases & Business Value
- **Reputation monitoring:** Track sentiment shifts over time for your own or competitor listings
- **NLP & sentiment datasets:** Build labeled training data from real-world hospitality reviews
- **Competitive benchmarking:** Compare ratings, response rates, and review volume across similar properties
- **Travel platforms:** Enrich aggregator listings with authentic guest feedback
- **Market research:** Analyze review language patterns by property type, region, or price tier
***
### Conclusion
The **Airbnb Reviews Scraper** transforms publicly available guest feedback into structured, analysis-ready data. With flexible sorting, pagination support, and rich 30+ field output per review, it covers everything from raw text to reviewer metadata and host responses. Whether you're tracking reputation, building datasets, or benchmarking competitors, this scraper delivers the review intelligence you need — efficiently and at scale.
# Actor input Schema
## `urls` (type: `array`):
Add the URLs of the Rooms details urls you want to scrape. You can paste URLs one by one, or use the Bulk edit section to add a prepared list.
## `sort_by` (type: `string`):
Select your option to sort reviews
## `offset` (type: `integer`):
Offset to start from
## `ignore_url_failures` (type: `boolean`):
If true, the scraper will continue running even if some URLs fail to be scraped.
## `max_items_per_url` (type: `integer`):
The maximum number of items to scrape per URL.
## Actor input object example
```json
{
"urls": [
"https://www.airbnb.com/rooms/12937?source_impression_id=p3_1779704219_P30eqXRfLO5jT57C&review_page_entrypoint=show_all"
],
"ignore_url_failures": true,
"max_items_per_url": 20
}
```
# 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 = {
"urls": [
"https://www.airbnb.com/rooms/12937?source_impression_id=p3_1779704219_P30eqXRfLO5jT57C&review_page_entrypoint=show_all"
],
"offset": 0,
"ignore_url_failures": true,
"max_items_per_url": 20
};
// Run the Actor and wait for it to finish
const run = await client.actor("stealth_mode/airbnb-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 = {
"urls": ["https://www.airbnb.com/rooms/12937?source_impression_id=p3_1779704219_P30eqXRfLO5jT57C&review_page_entrypoint=show_all"],
"offset": 0,
"ignore_url_failures": True,
"max_items_per_url": 20,
}
# Run the Actor and wait for it to finish
run = client.actor("stealth_mode/airbnb-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 '{
"urls": [
"https://www.airbnb.com/rooms/12937?source_impression_id=p3_1779704219_P30eqXRfLO5jT57C&review_page_entrypoint=show_all"
],
"offset": 0,
"ignore_url_failures": true,
"max_items_per_url": 20
}' |
apify call stealth_mode/airbnb-reviews-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=stealth_mode/airbnb-reviews-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Airbnb Reviews Scraper",
"description": "Scrape guest reviews from any Airbnb listing — including ratings, reviewer profiles, host responses, review media, and highlights. Collect up to 200 reviews per URL with flexible sorting and offset options. Perfect for hosts, analysts, and researchers.",
"version": "0.0",
"x-build-id": "b7fwIekmWc5iphxd1"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/stealth_mode~airbnb-reviews-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-stealth_mode-airbnb-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": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/stealth_mode~airbnb-reviews-scraper/runs": {
"post": {
"operationId": "runs-sync-stealth_mode-airbnb-reviews-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/stealth_mode~airbnb-reviews-scraper/run-sync": {
"post": {
"operationId": "run-sync-stealth_mode-airbnb-reviews-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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",
"properties": {
"urls": {
"title": "URLs of the Rooms details urls to scrape",
"type": "array",
"description": "Add the URLs of the Rooms details urls you want to scrape. You can paste URLs one by one, or use the Bulk edit section to add a prepared list.",
"items": {
"type": "string"
}
},
"sort_by": {
"title": "Sort by",
"enum": [
"BEST_QUALITY",
"MOST_RECENT",
"RATING_DESC",
"RATING_ASC"
],
"type": "string",
"description": "Select your option to sort reviews"
},
"offset": {
"title": "Offset",
"type": "integer",
"description": "Offset to start from"
},
"ignore_url_failures": {
"title": "Continue running even if some URLs fail to be scraped",
"type": "boolean",
"description": "If true, the scraper will continue running even if some URLs fail to be scraped."
},
"max_items_per_url": {
"title": "Max items per URL",
"type": "integer",
"description": "The maximum number of items to scrape per URL."
}
}
},
"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
}
}
}
}
}
}
}
}
}
}
```