TripAdvisor Reviews Scraper

TripAdvisor Reviews Scraper creates a structured dataset of hotel review records collected from tripadvisor.com. Each dataset item can include the review rating, title, body text, published date, language, helpful-vote count, reviewer name and avatar, trip details, and the management response when present. Query the source using hotel page URLs, control the result limit with maxItems, and retrieve records through the Apify Dataset API or export them as JSON, CSV, Excel, or XML.

Dataset at a glance

Property	Value
Source	tripadvisor.com
Record unit	One hotel review
Input methods	Hotel page URLs
Main identifiers	id, url
Delivery	Apify Dataset and API
Export formats	JSON, CSV, Excel, XML
Update model	Fresh records per Actor run
Pricing	Pay per event — $1 per 1,000 reviews

Coverage and available records

• Supported inputs — TripAdvisor hotel page URLs (https://www.tripadvisor.com/Hotel_Review-...).
• Pagination — Reviews are paginated through TripAdvisor's review endpoint until maxItems is reached or the hotel's reviews are exhausted.
• Language filter — language restricts results to a single ISO 639-1 language (en, es, fr, de, and others).
• Enrichment — Each review carries the reviewer's display name, avatar, profile URL, and trip details (stayDate, tripType) when available.
• Management responses — mgmtResponse captures the hotel's reply text and date when the property has responded.
• Not currently collected — Hotel metadata (rating, amenities, photos of the property) and reviewer profile pages.

Data dictionary

Field	Type	Nullable	Description	Example
id	number	No	Numeric review ID; best deduplication key	1071377162
url	string	No	Review URL	https://www.tripadvisor.com/ShowUserReviews-...
rating	number	Yes	Star rating (1–5)	5
title	string	Yes	Review title	Loved our stay!
text	string	Yes	Review body text	Great hotel. Very clean...
publishedDate	string	Yes	Review date (YYYY-MM-DD)	2026-08-03
language	string	Yes	Review language code	en
helpfulVotes	number	Yes	Helpful-vote count	0
tripInfo	object	Yes	Trip details (stayDate, tripType)	{ "stayDate": "2026-07-31", "tripType": "FAMILY" }
userDisplayName	string	Yes	Reviewer display name	Hali R
userAvatar	string	Yes	Reviewer avatar URL	https://dynamic-media-cdn.tripadvisor.com/...
userProfileUrl	string	Yes	Reviewer profile URL	https://www.tripadvisor.com/Profile/halir755
reviewUrl	string	Yes	Direct review detail URL	https://www.tripadvisor.com/ShowUserReviews-...
locationName	string	Yes	Hotel name	Crowne Plaza HY36 Midtown Manhattan by IHG
locationUrl	string	Yes	Hotel page URL	https://www.tripadvisor.com/Hotel_Review-...
photos	array	Yes	Review photos (often empty)	null
mgmtResponse	object	Yes	Management response (text, publishedDate)	{ "text": "...", "publishedDate": "2026-07-26" }

Example dataset record

{
  "id": 1071377162,
  "url": "https://www.tripadvisor.com/ShowUserReviews-g60763-d11854022-r1071377162-Crowne_Plaza_HY36_Midtown_Manhattan_by_IHG-New_York_City_New_York.html",
  "rating": 5,
  "title": "Loved our stay!",
  "text": "Great hotel. Very clean, staff was so nice and helpful.",
  "publishedDate": "2026-08-03",
  "language": "en",
  "helpfulVotes": 0,
  "tripInfo": { "stayDate": "2026-07-31", "tripType": "FAMILY" },
  "userDisplayName": "Hali R",
  "locationName": "Crowne Plaza HY36 Midtown Manhattan by IHG",
  "photos": null,
  "mgmtResponse": null
}

This record was produced from the hotel URL https://www.tripadvisor.com/Hotel_Review-g60763-d11854022-Reviews-Crowne_Plaza_HY36_Midtown_Manhattan_by_IHG-New_York_City_New_York.html.

Query and input reference

Input	Type	Required	Default	Accepted values	Description
startUrls	array	Yes	—	TripAdvisor hotel page URLs	Pages to scrape reviews from
maxItems	integer	No	0	0 = unlimited	Max reviews across all hotels
language	string	No	en	ISO 639-1 codes (en, es, fr, de, it, pt, nl, sv, da, no, fi, ja, zh, ko, ru, ar)	Language filter
proxyConfiguration	object	No	Residential	Apify proxy config	Residential proxies used by default

Minimal request:

{
  "startUrls": [
    { "url": "https://www.tripadvisor.com/Hotel_Review-g60763-d11854022-Reviews-Crowne_Plaza_HY36_Midtown_Manhattan_by_IHG-New_York_City_New_York.html" }
  ]
}

Advanced request:

{
  "startUrls": [
    { "url": "https://www.tripadvisor.com/Hotel_Review-g60763-d11854022-Reviews-Crowne_Plaza_HY36_Midtown_Manhattan_by_IHG-New_York_City_New_York.html" }
  ],
  "maxItems": 500,
  "language": "en",
  "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"] }
}

Retrieve the data through the API

1. Start the Actor with a JSON input via the Apify API or the Actor's API tab.
2. Wait for the run to finish.
3. Retrieve items from the run's default dataset.
4. Paginate or export the dataset in JSON, CSV, Excel, or XML.

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")
run = client.actor("datascrapers/tripadvisor-reviews-scraper").call(
    run_input={
        "startUrls": [{"url": "https://www.tripadvisor.com/Hotel_Review-g60763-d11854022-Reviews-Crowne_Plaza_HY36_Midtown_Manhattan_by_IHG-New_York_City_New_York.html"}],
        "maxItems": 200,
    }
)
items = client.dataset(run["defaultDatasetId"]).list_items().items

Data quality and record handling

• Completeness — Rating, title, text, and date are present on most reviews; tripInfo, photos, and mgmtResponse are conditional.
• Deduplication — Use id as the stable external key; url also works.
• Retries — TripAdvisor uses DataDome protection; residential proxies are used by default to reduce blocks.
• Normalization — rating and helpfulVotes are numbers; publishedDate uses YYYY-MM-DD.
• Raw vs derived — All fields are taken directly from TripAdvisor's review payload; no AI-generated or computed values are added.

Export and pipeline examples

Destination	Recommended method	Typical use
PostgreSQL/Supabase	Dataset API or webhook consumer	Review archive keyed by id
Google Sheets	Apify integration	Sentiment review of hotel feedback
S3/cloud storage	Scheduled export or integration	Periodic review ingestion for analytics

Pricing and cost examples

Billing is pay-per-event, tiered across Apify plans; the rate below is the free-plan rate.

Event	Charged when	Free-plan rate
dataset-item (Reviews)	A review is pushed to the dataset	$1 per 1,000 reviews

A fixed one-time Actor Start charge of $0.00005 also applies to each run.

Reviews	Estimated base cost
1,000	$1
10,000	$10

Estimates depend on the pricing model and the options enabled.

Limitations and responsible data use

• Only publicly accessible TripAdvisor review data is collected.
• Review availability depends on TripAdvisor's page structure and DataDome protection; results may be partial during aggressive blocking.
• photos and mgmtResponse are frequently empty and are conditional.
• No historical snapshots are stored unless you persist them yourself across scheduled runs.
• You are responsible for complying with TripAdvisor's terms and applicable privacy and data laws.

Dataset questions

What does one dataset item represent?

One hotel review. All reviews from each supplied hotel URL are paginated until maxItems is reached.

Which field should I use as a unique identifier?

id is the numeric review ID; url is a stable fallback.

Are fields nullable or conditional?

Yes. tripInfo, photos, and mgmtResponse are optional and frequently null; language reflects the filtered language.

Can I retrieve the records as CSV or JSON?

Yes. The default dataset can be exported as JSON, CSV, Excel, or XML from the Apify Console or via the Dataset API.

How do I paginate large datasets?

The Actor paginates reviews automatically up to maxItems. For very large exports, page through the dataset with the Dataset API offset and limit parameters.

What counts as a billable result?

Each review written to the dataset is one dataset-item event.

Related datasets from Data Scrapers

• OpenTable Scraper — restaurant listings and reviews for hospitality research.
• Yelp Scraper — business listings and reviews across categories.
• Google Play Store App Reviews Scraper — app review datasets for sentiment analysis.

Data Scrapers support

Need an additional field, record type, or export workflow? Contact Data Scrapers at stardustspotlight@gmail.com. Include a sample source URL, required fields, expected record volume, and preferred delivery format.