# TripAdvisor Reviews Dataset for NLP

**Use case:** 

Build a clean, labeled TripAdvisor reviews dataset for sentiment analysis and NLP. Each row gives review text, a 1–5 star label, sub-ratings and language — ready to export as CSV or JSON and feed straight into your model. Scale from a few hundred to thousands of reviews per listing.

## Input

```json
{
  "detailUrls": [
    "https://www.tripadvisor.com/Hotel_Review-g60763-d93450-Reviews-Hyatt_Grand_Central_New_York-New_York_City_New_York.html"
  ],
  "maxReviews": 500,
  "region": "United States",
  "currency": "U.S. Dollars",
  "sortBy": "Most recent",
  "searchQuery": "",
  "ratingFilter": [],
  "travelerType": [],
  "timeOfYear": [],
  "reviewLanguage": "en",
  "recentDays": 0,
  "autoTranslate": false
}
```

## Output

```json
{
  "locationId": {
    "label": "Location ID",
    "format": "text"
  },
  "locationName": {
    "label": "Location Name",
    "format": "text"
  },
  "locationAverageRating": {
    "label": "Location Average Rating",
    "format": "number"
  },
  "locationReviewCount": {
    "label": "Location Review Count",
    "format": "number"
  },
  "locationRatingCounts": {
    "label": "Rating Breakdown",
    "format": "object"
  },
  "reviewId": {
    "label": "Review ID",
    "format": "text"
  },
  "reviewUrl": {
    "label": "Review URL",
    "format": "link"
  },
  "title": {
    "label": "Title",
    "format": "text"
  },
  "text": {
    "label": "Text",
    "format": "text"
  },
  "rating": {
    "label": "Rating",
    "format": "number"
  },
  "additionalRatings": {
    "label": "Additional Ratings",
    "format": "object"
  },
  "publishedDate": {
    "label": "Published Date",
    "format": "date"
  },
  "createdDate": {
    "label": "Written On",
    "format": "date"
  },
  "travelDate": {
    "label": "Travel Date",
    "format": "text"
  },
  "tripType": {
    "label": "Trip Type",
    "format": "text"
  },
  "language": {
    "label": "Language",
    "format": "text"
  },
  "originalLanguage": {
    "label": "Original Language",
    "format": "text"
  },
  "translationType": {
    "label": "Translation",
    "format": "text"
  },
  "helpfulVotes": {
    "label": "Helpful Votes",
    "format": "number"
  },
  "photoUrls": {
    "label": "Photos",
    "format": "array"
  },
  "photoCount": {
    "label": "Photos",
    "format": "number"
  },
  "username": {
    "label": "Username",
    "format": "text"
  },
  "userLocation": {
    "label": "User Location",
    "format": "text"
  },
  "contributionCount": {
    "label": "Contributions",
    "format": "number"
  },
  "userHelpfulVotes": {
    "label": "Reviewer Helpful Votes",
    "format": "number"
  },
  "userProfileUrl": {
    "label": "User Profile",
    "format": "link"
  },
  "userAvatar": {
    "label": "User Avatar",
    "format": "image"
  },
  "ownerResponseName": {
    "label": "Owner Response Name",
    "format": "text"
  },
  "ownerResponseRole": {
    "label": "Responder Role",
    "format": "text"
  },
  "ownerResponseText": {
    "label": "Owner Response",
    "format": "text"
  },
  "ownerResponseDate": {
    "label": "Owner Response Date",
    "format": "date"
  },
  "cruiseLabels": {
    "label": "Cruise Labels",
    "format": "object"
  },
  "reviewTips": {
    "label": "Review Tips",
    "format": "array"
  },
  "attribution": {
    "label": "Collected With",
    "format": "text"
  },
  "page": {
    "label": "Page",
    "format": "number"
  },
  "crawledAt": {
    "label": "Crawled At",
    "format": "text"
  },
  "detailUrl": {
    "label": "Detail Page URL",
    "format": "link"
  }
}
```

## About this Actor

This example demonstrates how to use [TripAdvisor Reviews Scraper - All 5 Categories](https://apify.com/delicious_zebu/tripadvisor-review-collector.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/delicious_zebu/tripadvisor-review-collector.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

This Task's input is already configured above. Use it as-is rather than inventing a new one.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/delicious_zebu/tripadvisor-review-collector.md

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).