# Hotel Sentiment Analysis Dataset from Booking.com

**Use case:** 

Booking asks guests what they liked and what they did not, and stores the two answers apart - so the sentiment is labelled before any model sees it. Ninety written reviews of one London hotel with positives, negatives, score, language and traveller type: a training or evaluation set for aspect-level sentiment, no annotation needed. Cost: 90 review rows at $0.005 = at most $0.45 a run.

## Input

```json
{
  "startUrls": [],
  "hotelNames": [
    "The Ritz London"
  ],
  "hotelIds": [],
  "maxReviewsPerHotel": 90,
  "reviewsSort": "most_recent",
  "languages": [],
  "travelerType": "all",
  "keyword": "",
  "maxRating": 0,
  "requireText": true,
  "locale": "en-US",
  "includeHotelRow": true,
  "sessions": 4,
  "perIp": 1,
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}
```

## Output

```json
{
  "hotel_name": {
    "label": "Hotel name",
    "format": "string"
  },
  "rating": {
    "label": "Rating",
    "format": "number"
  },
  "rating_5": {
    "label": "Rating 5",
    "format": "number"
  },
  "title": {
    "label": "Title",
    "format": "string"
  },
  "positives": {
    "label": "Positives",
    "format": "string"
  },
  "negatives": {
    "label": "Negatives",
    "format": "string"
  },
  "language": {
    "label": "Language",
    "format": "string"
  },
  "review_date": {
    "label": "Review date",
    "format": "string"
  },
  "check_in": {
    "label": "Check in",
    "format": "string"
  },
  "nights": {
    "label": "Nights",
    "format": "integer"
  },
  "room_type": {
    "label": "Room type",
    "format": "string"
  },
  "traveler_type": {
    "label": "Traveler type",
    "format": "string"
  },
  "reviewer_name": {
    "label": "Reviewer name",
    "format": "string"
  },
  "reviewer_country": {
    "label": "Reviewer country",
    "format": "string"
  },
  "helpful_votes": {
    "label": "Helpful votes",
    "format": "integer"
  },
  "response": {
    "label": "Response",
    "format": "string"
  }
}
```

## About this Actor

This example demonstrates how to use [Booking.com Reviews Scraper — Hotel Guest Reviews & Ratings](https://apify.com/kestrel/booking-reviews-scraper.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/kestrel/booking-reviews-scraper.md) to learn more, explore other use cases, and run it yourself.


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For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/kestrel/booking-reviews-scraper.md

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).