TripAdvisor Reviews [Only $0.45💰] Scraper

TripAdvisor Reviews Scraper

Turn TripAdvisor hotel pages into structured review datasets. Pull every public review for a property — title, rating, language, text, travel date, owner response, photos, sub‑ratings — already enriched with the host place's full metadata (address, geo, ranking, ratingHistogram). One run, one clean dataset.

How it works

✨ Why use this scraper?

Manually opening hotel pages and copying reviews? Stitching together separate "reviews" and "place details" scrapes? Getting blocked by DataDome the moment you scale?

• 🏨 Reviews + place metadata in the same row. Every review already carries placeInfo (rating, address, lat/lng, ranking, histogram). No follow‑up enrichment.
• 🎯 Server‑side filters wired through TripAdvisor's GraphQL. Star ratings, languages, per‑place limits and dates are pushed down to the API — you get back what you asked for.
• 📅 Absolute or relative date cutoff. "2026-01-01" or "22 days", "3 weeks", "6 months", "1 year" — all valid for lastReviewDate.
• 👤 Optional reviewer profiles. Flip scrapeReviewerInfo to switch from the lean review‑centric output to a reviewer‑centric output with username, hometown, contributions, avatar, profile link.
• 🛡️ Hardened anti‑bot path. Mobile‑Safari UA fallback through undici for HTML, real browser fingerprinting via ImpitHttpClient for the GraphQL endpoint, single‑shot DataDome detection.
• 📑 Per‑location failure dataset. Skipped or blocked hotels land in a side dataset (tripadvisor-failures) instead of getting buried in logs.
• ⚡ Parallel pagination. Each hotel pages through GraphQL in concurrent batches (default 3), respecting your global and per‑place caps.

🎯 Use cases

Team	What they build
Hotel ops	Daily review monitoring + owner‑response SLA tracking
Reputation managers	Multi‑property reputation dashboards with ratingHistogram drift over time
Market analysts	Competitive benchmarks across cities or chains using placeInfo.rating + numberOfReviews
Content / NLP teams	Multilingual review corpora for sentiment and topic models, filtered by language and rating
Travel media	Curated "best of" articles backed by recent verified reviews
Data teams	One‑shot dataset exports for BI, lake or warehouse ingestion (JSON, CSV, Excel)

🔧 How it works (pipeline)

1. Detect location ID from each *_Review-... URL (-d{id}-) — works for hotels, restaurants and attractions.
2. Fetch the place HTML with a mobile‑Safari User‑Agent. Falls back to a direct undici fetch when DataDome blocks the desktop fingerprint, and to URL‑derived placeInfo when even that is blocked (reviews still come through over GraphQL).
3. Extract placeInfo from the page's JSON‑LD + meta description (rating, review count, address, geo, ranking position).
4. Page through GraphQL reviews at /data/graphql/ids in concurrent batches, with reviewRatings / reviewsLanguages / maxItemsPerQuery pushed into the filter payload.
5. Apply lastReviewDate client‑side after each page, and break early once an entire page is older than the cutoff.
6. Map and push each review enriched with placeInfo to the default dataset; skipped or blocked places go to tripadvisor-failures.

📥 Supported inputs

Currently supported start URLs (mix and match in a single run):

Pattern	Example
Hotel_Review-g{geoId}-d{locationId}-Reviews-{slug}.html	https://www.tripadvisor.com/Hotel_Review-g60763-d208453-Reviews-Hilton_New_York_Times_Square-New_York_City_New_York.html
Restaurant_Review-g{geoId}-d{locationId}-Reviews-{slug}.html	https://www.tripadvisor.com/Restaurant_Review-g60763-d25324283-Reviews-Allora_Fifth_Ave-New_York_City_New_York.html
Attraction_Review-g{geoId}-d{locationId}-Reviews-{slug}.html	https://www.tripadvisor.com/Attraction_Review-g60763-d105123-Reviews-Statue_of_Liberty-New_York_City_New_York.html

All three share the same GraphQL endpoint and review schema — only placeInfo.type differs (HOTEL, EATERY, ATTRACTION).

Not currently supported:

• Search / list pages (FindRestaurants?..., Hotels-g…, Attractions-g…).
• tripadvisor.co.* country domains (use .com).
• Non‑TripAdvisor hosts.

⚙️ Input parameters

Required

Parameter	Type	Default	Description
startUrls	array of { url }	—	One or more TripAdvisor place URLs (Hotel_Review-…, Restaurant_Review-…, or Attraction_Review-…). Run them in parallel up to maxConcurrency.

Filters

Parameter	Type	Default	Description
maxItemsPerQuery	integer	50	Max reviews to fetch per place. 0 = unlimited (paginate to the end).
reviewRatings	array	[] (all)	Star ratings to keep. Values: "1", "2", "3", "4", "5", or "ALL_REVIEW_RATINGS". Pushed down into the GraphQL filter payload.
reviewsLanguages	array	[] (all)	ISO 639‑1 codes (e.g. ["en", "de", "fr"]) or "ALL_REVIEW_LANGUAGES". Pushed down into the GraphQL filter payload.
lastReviewDate	string	—	Skip reviews published before this date. Accepts an absolute date YYYY-MM-DD or a relative duration: "22 days", "2 weeks", "3 months", "1 year" (singular or plural).
scrapeReviewerInfo	boolean	true	When true, the user object on each review is populated with the reviewer's profile (username, display name, avatar, hometown, contributions, profile link). When false, user is null. The rest of the review fields (id, lang, helpfulVotes, tripType, subratings, photos, …) are emitted in both modes.

Advanced

Parameter	Type	Default	Description
maxItems	integer	10000	Hard ceiling on the total number of items written to the dataset across all places. 0 = no global cap.
maxConcurrency	integer	100	Max start URLs (hotels) processed concurrently.
minConcurrency	integer	1	Crawler floor.
maxRequestRetries	integer	15 (range 0–50)	Retries per request before giving up. Lower = surface failures fast, higher = absorb transient anti‑bot blocks.
proxy	object	{ useApifyProxy: true, apifyProxyGroups: ["RESIDENTIAL"] }	Standard Apify proxy block. Apify Residential is strongly recommended for TripAdvisor.

📊 Output overview

Each dataset row is one review enriched with the host place's placeInfo. The full review schema is emitted in both scrapeReviewerInfo modes — the only difference is whether the user object is populated (true) or set to null (false).

Review schema (both modes)

{
    "id": "1003456789",
    "url": "https://www.tripadvisor.com/ShowUserReviews-g60763-d208453-r1003456789-Hilton_New_York_Times_Square-New_York_City_New_York.html",
    "title": "Great location, friendly staff",
    "lang": "en",
    "language": "en",
    "originalLanguage": "en",
    "locationId": "208453",
    "publishedDate": "2026-03-14",
    "publishedPlatform": "OTHER",
    "rating": 5,
    "helpfulVotes": 2,
    "text": "We stayed three nights and...",
    "travelDate": "2026-03",
    "stayDate": "2026-03-14",
    "tripType": "COUPLES",
    "user": null,
    "ownerResponse": {
        "id": "987654",
        "text": "Thank you for staying with us...",
        "lang": "en",
        "publishedDate": "2026-03-16",
        "responder": "Hilton Times Square",
        "connectionToSubject": "Manager"
    },
    "subratings": [
        { "name": "Service", "value": 5 },
        { "name": "Cleanliness", "value": 5 },
        { "name": "Value", "value": 4 },
        { "name": "Location", "value": 5 },
        { "name": "Rooms", "value": 4 },
        { "name": "Sleep Quality", "value": 5 }
    ],
    "photos": [
        { "id": "812340000", "width": 4032, "height": 3024, "image": "https://media-cdn.tripadvisor.com/media/photo-o/30/68/0c/00/lobby.jpg" }
    ],
    "placeInfo": {
        "id": "208453",
        "name": "Hilton New York Times Square",
        "rating": 4.0,
        "numberOfReviews": 8944,
        "locationString": "New York City, New York",
        "latitude": 40.756,
        "longitude": -73.989,
        "webUrl": "https://www.tripadvisor.com/Hotel_Review-g60763-d208453-Reviews-Hilton_New_York_Times_Square-New_York_City_New_York.html",
        "website": "https://www.hilton.com/...",
        "address": "234 W 42nd St, New York City, NY 10036",
        "addressObj": {
            "street1": "234 W 42nd St",
            "city": "New York City",
            "state": "NY",
            "postalcode": "10036",
            "country": "United States"
        },
        "ratingHistogram": { "count1": 412, "count2": 480, "count3": 1100, "count4": 2680, "count5": 4272 }
    }
}

With scrapeReviewerInfo: true the only field that changes is user — it is replaced with the reviewer's profile object:

{
    "user": {
        "userId": "ABCDEF12345",
        "name": "Traveler 123",
        "contributions": { "totalContributions": 42 },
        "username": "traveler123",
        "userLocation": { "shortName": "Berlin", "name": "Berlin, Germany", "id": "187323" },
        "avatar": { "id": "5567890", "width": 200, "height": 200, "image": "https://media-cdn.tripadvisor.com/media/photo-l/...jpg" },
        "link": "www.tripadvisor.com/Profile/traveler123"
    }
}

🗂️ Output fields

Review core

All fields below are emitted in both scrapeReviewerInfo modes.

Field	Type	Description
id	string	TripAdvisor review ID
url	string	Permalink to the review on TripAdvisor
title	string	Review headline
text	string	Review body
rating	integer (1–5)	Stars left by the reviewer
lang	string (ISO 639‑1)	Source language (preserves originalLanguage for machine‑translated reviews)
language	string (ISO 639‑1)	Current API language (may be the translated language)
originalLanguage	string (ISO 639‑1)	Source language before machine translation
publishedDate	string (ISO date)	When the review was published
publishedPlatform	string	Source platform (e.g. OTHER, MOBILE)
helpfulVotes	integer	Helpful‑vote count
travelDate	string (YYYY-MM)	Month/year of the stay
stayDate	string (YYYY-MM-DD)	Full stay date
tripType	string | null	COUPLES, FAMILY, BUSINESS, SOLO, FRIENDS, …
locationId	string	TripAdvisor location ID for the place

Owner response

Field	Type	Description
ownerResponse.id	string	Response ID
ownerResponse.text	string	Response body
ownerResponse.lang	string	Response language
ownerResponse.publishedDate	string	Response date
ownerResponse.responder	string	Display name (e.g. property name or manager)
ownerResponse.connectionToSubject	string	Manager, Owner, etc.

Subratings

subratings is an array of { name, value }:

Field	Type	Description
subratings[].name	string	Service, Cleanliness, Value, Location, Rooms, Sleep Quality, …
subratings[].value	integer (1–5)	Per‑aspect rating

Photos

photos is an array of { id, width, height, image }:

Field	Type	Description
photos[].id	string	TripAdvisor photo ID
photos[].width / height	integer	Native pixel dimensions
photos[].image	string	Bare CDN URL (no ?w=... query)

Reviewer (only when scrapeReviewerInfo: true)

Field	Type	Description
user.userId	string | null	Internal TripAdvisor user ID
user.name	string | null	Display name
user.username	string | null	URL handle
user.contributions.totalContributions	integer	Lifetime contribution count
user.userLocation	object | null	{ shortName, name, id } resolved from hometown
user.avatar	object | null	{ id, width, height, image }
user.link	string | null	Profile link without scheme (www.tripadvisor.com/Profile/...)

Place metadata (placeInfo)

Field	Type	Description
placeInfo.id	string	Numeric location ID
placeInfo.name	string	Hotel name
placeInfo.rating	number	Aggregate 1–5 rating
placeInfo.numberOfReviews	integer	Total review count on TripAdvisor
placeInfo.locationString	string	Human‑readable city/state/country
placeInfo.latitude / longitude	number	Geo coordinates
placeInfo.address	string	Single‑line address
placeInfo.addressObj	object	{ street1, street2, city, state, postalcode, country }
placeInfo.website	string	Hotel's official website
placeInfo.webUrl	string	TripAdvisor URL
placeInfo.ratingHistogram	object	{ count1, count2, count3, count4, count5 }

🚀 Examples

Single hotel, defaults

{
    "startUrls": [
        { "url": "https://www.tripadvisor.com/Hotel_Review-g60763-d208453-Reviews-Hilton_New_York_Times_Square-New_York_City_New_York.html" }
    ],
    "maxItemsPerQuery": 50
}

Multiple hotels, English‑only, last 30 days

{
    "startUrls": [
        { "url": "https://www.tripadvisor.com/Hotel_Review-g60763-d208453-Reviews-Hilton_New_York_Times_Square-New_York_City_New_York.html" },
        { "url": "https://www.tripadvisor.com/Hotel_Review-g60763-d93589-Reviews-The_Manhattan_at_Times_Square_Hotel-New_York_City_New_York.html" }
    ],
    "maxItemsPerQuery": 100,
    "reviewsLanguages": ["en"],
    "lastReviewDate": "30 days"
}

Recent 3‑star reviews with full reviewer profiles

{
    "startUrls": [
        { "url": "https://www.tripadvisor.com/Hotel_Review-g60763-d208453-Reviews-Hilton_New_York_Times_Square-New_York_City_New_York.html" }
    ],
    "maxItemsPerQuery": 50,
    "reviewRatings": ["3"],
    "reviewsLanguages": ["en"],
    "lastReviewDate": "2026-01-01",
    "scrapeReviewerInfo": true
}

Mix hotels and restaurants in one run

{
    "startUrls": [
        { "url": "https://www.tripadvisor.com/Hotel_Review-g60763-d208453-Reviews-Hilton_New_York_Times_Square-New_York_City_New_York.html" },
        { "url": "https://www.tripadvisor.com/Restaurant_Review-g60763-d25324283-Reviews-Allora_Fifth_Ave-New_York_City_New_York.html" }
    ],
    "maxItemsPerQuery": 50,
    "reviewsLanguages": ["en"]
}

💻 Integrations

Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")

run = client.actor("muhamed-didovic/apify-tripadvisor").call(run_input={
    "startUrls": [
        {"url": "https://www.tripadvisor.com/Hotel_Review-g60763-d208453-Reviews-Hilton_New_York_Times_Square-New_York_City_New_York.html"},
    ],
    "maxItemsPerQuery": 50,
    "reviewsLanguages": ["en"],
    "lastReviewDate": "30 days",
})

for review in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"{review['rating']}★  {review['title']}  ({review['lang']})")
    print(f"   place: {review['placeInfo']['name']}  rating: {review['placeInfo']['rating']}")

JavaScript / Node

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_API_TOKEN' });

const run = await client.actor('muhamed-didovic/apify-tripadvisor').call({
    startUrls: [
        { url: 'https://www.tripadvisor.com/Hotel_Review-g60763-d208453-Reviews-Hilton_New_York_Times_Square-New_York_City_New_York.html' },
    ],
    maxItemsPerQuery: 50,
    scrapeReviewerInfo: true,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((r) => {
    console.log(`${r.rating}★  ${r.title}  by ${r.user?.username ?? 'anon'}`);
});

📈 Performance

Metric	Value
Reviews per hotel page (GraphQL)	10
Concurrent review pages per hotel	up to 3 (auto‑capped to 1 when many hotels run in parallel)
Anti‑bot path	Mobile‑Safari UA + ImpitHttpClient GraphQL fingerprint, single‑shot DataDome detection
Failure visibility	Per‑location rows in tripadvisor-failures named dataset
Output formats	JSON, CSV, Excel, RSS, XML, HTML (via Apify dataset views)

💡 Tips for best results

1. Start with one place and maxItemsPerQuery: 10 to validate the schema. Works the same for hotels, restaurants and attractions — confirm the fields you care about land in the dataset before launching big runs.
2. Use server‑side filters. reviewRatings and reviewsLanguages are pushed into the GraphQL payload — much cheaper than fetching everything and filtering downstream.
3. Prefer relative dates over absolute when running on a schedule. "30 days" always means "last 30 days from now"; an absolute 2026-01-01 will silently widen as time passes.
4. Lower maxRequestRetries for fast feedback. The default 15 absorbs anti‑bot blocks but can hide a misconfigured proxy. Try 3 while iterating, raise it for production.
5. Toggle scrapeReviewerInfo only when you need profiles. All review fields are kept in both modes; the only thing that changes is whether user is populated. Disabling it makes the dataset smaller and the run faster.
6. Check the tripadvisor-failures dataset after each run. Empty = perfect run. Rows = location‑level issues you can replay.

❓ FAQ

Which TripAdvisor URLs are supported? Hotel_Review-…, Restaurant_Review-…, and Attraction_Review-… URLs on www.tripadvisor.com (anything that follows the …-g{geoId}-d{locationId}-Reviews-… slug pattern). They share the same GraphQL endpoint and review schema — only placeInfo.type differs (HOTEL / EATERY / ATTRACTION). Search/list pages and tripadvisor.co.* country domains are not supported — use .com.

How many reviews can I scrape per run? As many as your Apify plan and maxItems / maxItemsPerQuery allow. The actor paginates TripAdvisor's GraphQL API in batches of 10 per request, in parallel where possible.

What does scrapeReviewerInfo actually change? The only field that changes is user. With true (default) the user object is populated with the reviewer's profile (username, display name, avatar, hometown, contributions, profile link). With false it's null. All other review fields (id, lang, subratings, photos, helpfulVotes, tripType, …) are emitted in both modes.

What date formats does lastReviewDate accept? Both absolute (2026-01-01, ISO YYYY-MM-DD) and relative durations: "22 days", "3 weeks", "6 months", "1 year" (singular and plural both work). Reviews older than the resolved date are dropped client‑side, with an early‑break optimisation that stops paginating once an entire page is older than the cutoff.

Why is lang sometimes different from the on‑site language toggle? TripAdvisor machine‑translates reviews. We always emit the source language (originalLanguage), not the displayed translation, so analytics groupings stay accurate.

Can I scrape multiple places in one run? Yes — pass any number of startUrls. Hotels, restaurants and attractions can be mixed in the same run; they're processed concurrently up to maxConcurrency. Intra‑place pagination is auto‑capped to 1 in that case so the GraphQL endpoint isn't hammered with concurrency × pages requests.

Where do failed locations end up? In a named dataset called tripadvisor-failures with rows like { url, locationId, locationType, reason, message, timestamp }. The reason field is one of invalid-location-id, html-blocked, datadome-block, reviews-fetch-failed, no-reviews-saved. The Apify run page surfaces a direct link.

Is private content accessible? No. The actor only sees public TripAdvisor pages and the public review GraphQL endpoint.

📬 Support

• Bug reports / feature requests: use the Issues tab on the actor page.
• Direct contact: muhamed.didovic@gmail.com
• Author's website: muhamed-didovic.github.io

🛠️ Additional services

• Custom output schemas, one‑off datasets, scheduled exports.
• Other platforms (Booking, Yelp, Google Maps, etc.) on request.
• API integrations and automation pipelines.

Email: muhamed.didovic@gmail.com.

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⚖️ Legal & compliance

This scraper targets publicly accessible TripAdvisor content for legitimate research, monitoring, and analytics. You are responsible for:

• Complying with TripAdvisor's terms of service.
• Respecting robots.txt and reasonable rate limits.
• Using scraped data lawfully (privacy, copyright, GDPR/CCPA where applicable).
• Obtaining any necessary permissions for commercial reuse of the data.