# Tripadvisor Reviews (`datasaurus/tripadvisor-reviews`) Actor Scrape reviews from Tripadvisor for Hotels and Restaurants. Filter by language, rating, traveller type, and time of year. Sort by most recent or most detailed. Fast and efficient. n8n node: n8n-nodes-tripadvisor-reviews - **URL**: https://apify.com/datasaurus/tripadvisor-reviews.md - **Developed by:** [datasaurus](https://apify.com/datasaurus) (community) - **Categories:** Travel - **Stats:** 28 total users, 3 monthly users, 94.1% runs succeeded, 2 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing $12.00/month + usage To use this Actor, you pay a monthly rental fee to the developer. The rent is subtracted from your prepaid usage every month after the free trial period.You also pay for the Apify platform usage, which gets cheaper the higher Apify subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#rental-actors ## 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 ## Tripadvisor Reviews Scraper This tool scrapes Hotel and Resturant reviews from Tripadvisor. Also outputs review aggregations for each location into the key-value store. n8n node: [n8n-nodes-tripadvisor-reviews](https://www.npmjs.com/package/n8n-nodes-tripadvisor-reviews) ### Features - **Reliability**: - Designed efficiency and reliability, using residential proxies, dynamic request headers and session pooling to avoid IP blocking. - **Granularity**: - Sort by sorting most relevant or most recent. Filter by langague, rating, traveller_type, time_of_year. - **Multiple URLs**: Scrape data from multiple start URLs within a single run. - **Set Limits**: Define the maximum number of reviews to scrape per URL. ### Notes - Output is in JSON format due to the nested data structure. - The field names match the field names returned by Tripadvisor. ### Example Input ```json { "start_urls": [ {"url": "https://www.tripadvisor.co.uk/Hotel_Review-g60763-d6510520-Reviews-Hilton_Garden_Inn_New_York_Midtown_Park_Ave-New_York_City_New_York.html"}, {"url": "https://www.tripadvisor.co.uk/Restaurant_Review-g60763-d7890999-Reviews-or15-Kuu_Ramen-New_York_City_New_York.html"} ], "original_language": "it", "sort_type": "Most Recent", "keywords": "", "traveller_rating": ["1", "2", "3", "4", "5"], "time_of_year": ["January", "February", "March"], "max_results": 100 } ```` #### Example Output ```json [ { "id": 997181633, "locationId": 6510520, "status": "PUBLISHED", "createdDate": "2025-03-08", "publishedDate": "2025-03-08", "rating": 4, "title": "My Hilton Stay (1 King Bdrm, February 2025)", "text": "Perfect location! Right across the street from the 6 subway line. It was easy to get downtown and uptown. \n\nThe room was small but that’s to be expected in NYC. Very clean and my view was great. \n\nThe staff were helpful and friendly. However the restaurant next door (which is part of the hotel) will get a little busy. I was sitting at the bar for the a good 10 minutes with no “hello” or “I’ll be right with you.” I ended up leaving but I did return the following day for a drink \n\nA little noisy. Right now this hotel is going through a renovation process. I heard a lot of equipment machinery from the floors above. Also the walls are pretty thin. There was a group staying in the room near me and they were loud as hell. The door slams and it’s loud too. Basically you can hear anything. \n\nBesides the noise and the busy restaurant it was a good stay. I would stay again.", "reviewTip": { "responseData": { "tips": [ { "body": "Across the street from the subway \n\nConcierge will hold you bags after check out if you have a late flight", "published": true } ] } }, "language": "en", "originalLanguage": "en", "translationType": null, "url": "https://www.tripadvisor.co.uk/ShowUserReviews-g60763-d6510520-r997181633-Hilton_Garden_Inn_New_York_Midtown_Park_Ave-New_York_City_New_York.html", "location": { "locationId": 6510520, "name": "Hilton Garden Inn New York/Midtown Park Ave", "placeType": "ACCOMMODATION", "accommodationCategory": "HOTEL", "businessAdvantageData": { "favoriteReview": { "reviewId": 1009933303 } } }, "publishPlatform": "MOBILE", "connectionToSubject": null, "userProfile": { "id": "C2280073D8CDCDBF94C12B948CEA3733", "isVerified": false, "displayName": "Jonathan S", "username": "jmsinatra1", "avatar": { "__typename": "MemberProfile_MediaId", "data": { "__typename": "Media_PhotoResult", "id": 452388669, "photoSizeDynamic": { "urlTemplate": "https://dynamic-media-cdn.tripadvisor.com/media/photo-o/1a/f6/e7/3d/default-avatar-2020-55.jpg?w={width}&h={height}&s=1", "maxHeight": 1200, "maxWidth": 1200 } } }, "hometown": { "locationId": 32999, "fallbackString": "32999", "location": { "locationId": 32999, "additionalNames": { "name": "Sacramento", "long": "Sacramento, California" } } }, "route": { "url": "/Profile/jmsinatra1" }, "contributionCounts": { "sumAllUgc": 8 } }, "mgmtResponse": { "id": 997434150, "text": "jmsinatra1, thank you for your recent Trip Advisor review! My team and I are glad that you enjoyed your time with us! We do hope for another opportunity to serve you again in the future!", "language": "en", "translationType": null, "publishedDate": "2025-03-10", "username": "Jon Schorr", "connectionToSubject": "Owner", "userProfile": { "userId": "36CF052EAC1B650B840F1BCC62C222B8", "route": { "url": "/Profile/JonSchorr" }, "avatar": { "__typename": "MemberProfile_MediaId", "data": { "__typename": "Media_PhotoResult", "id": 452391234, "photoSizeDynamic": { "urlTemplate": "https://dynamic-media-cdn.tripadvisor.com/media/photo-o/1a/f6/f1/42/default-avatar-2020-20.jpg?w={width}&h={height}&s=1", "maxHeight": 1200, "maxWidth": 1200 } } } } }, "helpfulVotes": 0, "labels": [], "attribution": null, "mtProviderId": 0, "alertStatus": false, "tripInfo": { "stayDate": "2025-03-31", "tripType": "SOLO" }, "additionalRatings": [], "photos": [ { "photo": { "__typename": "Media_PhotoResult", "id": 792700165, "photoSizeDynamic": { "urlTemplate": "https://dynamic-media-cdn.tripadvisor.com/media/photo-o/2f/3f/a5/05/caption.jpg?w={width}&h={height}&s=1", "maxWidth": 1536, "maxHeight": 2048 }, "caption": "", "albumId": 100, "statuses": [ "PUBLISHED" ] } }, { "photo": { "__typename": "Media_PhotoResult", "id": 792700166, "photoSizeDynamic": { "urlTemplate": "https://dynamic-media-cdn.tripadvisor.com/media/photo-o/2f/3f/a5/06/caption.jpg?w={width}&h={height}&s=1", "maxWidth": 1536, "maxHeight": 2048 }, "caption": "", "albumId": 100, "statuses": [ "PUBLISHED" ] } }, { "photo": { "__typename": "Media_PhotoResult", "id": 792700167, "photoSizeDynamic": { "urlTemplate": "https://dynamic-media-cdn.tripadvisor.com/media/photo-o/2f/3f/a5/07/caption.jpg?w={width}&h={height}&s=1", "maxWidth": 1536, "maxHeight": 2048 }, "caption": "", "albumId": 100, "statuses": [ "PUBLISHED" ] } } ] } ] ``` ### Automation See this YouTube [video](https://youtu.be/z6CFGweDgsE?si=JzHuTEBXMt-DkWzO) on how to intergrate scrappers with Make.com, Chat-GPT and Google Sheets. # Actor input Schema ## `start_urls` (type: `array`): Review page urls ## `sort_type` (type: `string`): Sort Type. Default matches the website sort order. For Hotels this is 'most relevant'. For Resturants this is 'most recent'. ## `keywords` (type: `string`): Keywords ## `original_language` (type: `array`): Filter by the original language the reivew was written in. Default is all languages. ## `traveller_rating` (type: `array`): Traveller Rating. Default is all ratings ## `traveller_type` (type: `array`): Traveller Type. Default is all traveller types. ## `time_of_year` (type: `array`): Time of Year ## `deduplicate_results` (type: `boolean`): This may reduce the total number of results to less than max\_results if there are duplicates found. ## `max_results` (type: `integer`): Select the maximum number of reviews to scrape per url. ## Actor input object example ```json { "start_urls": [ { "url": "https://www.tripadvisor.co.uk/Hotel_Review-g60763-d6510520-Reviews-Hilton_Garden_Inn_New_York_Midtown_Park_Ave-New_York_City_New_York.html" }, { "url": "https://www.tripadvisor.co.uk/Restaurant_Review-g60763-d7890999-Reviews-or15-Kuu_Ramen-New_York_City_New_York.html" } ], "deduplicate_results": true, "max_results": 10 } ``` # Actor output Schema ## `results` (type: `string`): No description # 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 = { "start_urls": [ { "url": "https://www.tripadvisor.co.uk/Hotel_Review-g60763-d6510520-Reviews-Hilton_Garden_Inn_New_York_Midtown_Park_Ave-New_York_City_New_York.html" }, { "url": "https://www.tripadvisor.co.uk/Restaurant_Review-g60763-d7890999-Reviews-or15-Kuu_Ramen-New_York_City_New_York.html" } ], "max_results": 10 }; // Run the Actor and wait for it to finish const run = await client.actor("datasaurus/tripadvisor-reviews").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 = { "start_urls": [ { "url": "https://www.tripadvisor.co.uk/Hotel_Review-g60763-d6510520-Reviews-Hilton_Garden_Inn_New_York_Midtown_Park_Ave-New_York_City_New_York.html" }, { "url": "https://www.tripadvisor.co.uk/Restaurant_Review-g60763-d7890999-Reviews-or15-Kuu_Ramen-New_York_City_New_York.html" }, ], "max_results": 10, } # Run the Actor and wait for it to finish run = client.actor("datasaurus/tripadvisor-reviews").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 '{ "start_urls": [ { "url": "https://www.tripadvisor.co.uk/Hotel_Review-g60763-d6510520-Reviews-Hilton_Garden_Inn_New_York_Midtown_Park_Ave-New_York_City_New_York.html" }, { "url": "https://www.tripadvisor.co.uk/Restaurant_Review-g60763-d7890999-Reviews-or15-Kuu_Ramen-New_York_City_New_York.html" } ], "max_results": 10 }' | apify call datasaurus/tripadvisor-reviews --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=datasaurus/tripadvisor-reviews", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Tripadvisor Reviews", "description": "Scrape reviews from Tripadvisor for Hotels and Restaurants. Filter by language, rating, traveller type, and time of year. Sort by most recent or most detailed. Fast and efficient. n8n node: n8n-nodes-tripadvisor-reviews", "version": "0.3", "x-build-id": "qocMapu3HBQtznPos" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/datasaurus~tripadvisor-reviews/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-datasaurus-tripadvisor-reviews", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/datasaurus~tripadvisor-reviews/runs": { "post": { "operationId": "runs-sync-datasaurus-tripadvisor-reviews", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/datasaurus~tripadvisor-reviews/run-sync": { "post": { "operationId": "run-sync-datasaurus-tripadvisor-reviews", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "start_urls", "max_results" ], "properties": { "start_urls": { "title": "Review Page URLS", "uniqueItems": true, "type": "array", "description": "Review page urls", "default": [ { "url": "https://www.tripadvisor.co.uk/Hotel_Review-g60763-d6510520-Reviews-Hilton_Garden_Inn_New_York_Midtown_Park_Ave-New_York_City_New_York.html" } ], "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "sort_type": { "title": "Sort Type", "enum": [ "Most Recent", "Detailed Reviews" ], "type": "string", "description": "Sort Type. Default matches the website sort order.\nFor Hotels this is 'most relevant'.\nFor Resturants this is 'most recent'." }, "keywords": { "title": "Keywords", "type": "string", "description": "Keywords" }, "original_language": { "title": "Original Language", "type": "array", "description": "Filter by the original language the reivew was written in.\nDefault is all languages.", "items": { "type": "string", "enum": [ "en", "fr", "es", "de", "it", "ja", "zhCN", "zhTW", "sv", "nl", "pt", "tr", "da", "no", "pl", "th", "ko", "ru", "el", "in", "ar", "vi", "cs", "sk", "sr", "iw", "fi", "hu", "uk" ], "enumTitles": [ "English", "French", "Spanish", "German", "Italian", "Japanese", "Chinese (Sim.)", "Chinese (Trad.)", "Swedish", "Dutch", "Portuguese", "Turkish", "Danish", "Norwegian", "Polish", "Thai", "Korean", "Russian", "Greek", "Indonesian", "Arabic", "Vietnamese", "Czech", "Slovak", "Serbian", "Hebrew", "Finnish", "Hungarian", "Ukranian" ] } }, "traveller_rating": { "title": "Traveller Rating", "type": "array", "description": "Traveller Rating. Default is all ratings", "items": { "type": "string", "enum": [ "1", "2", "3", "4", "5" ] } }, "traveller_type": { "title": "Traveller Type", "type": "array", "description": "Traveller Type. Default is all traveller types.", "items": { "type": "string", "enum": [ "Business", "Couples", "Family", "Friends", "Solo" ] } }, "time_of_year": { "title": "Time of Year", "type": "array", "description": "Time of Year", "items": { "type": "string", "enum": [ "January", "February", "March", "April", "May", "June", "July", "August", "September", "October", "November", "December" ] } }, "deduplicate_results": { "title": "Deduplicate results", "type": "boolean", "description": "This may reduce the total number of results to less than max_results if there are duplicates found.", "default": true }, "max_results": { "title": "Max Results per review url", "minimum": 1, "maximum": 2000, "type": "integer", "description": "Select the maximum number of reviews 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 } } } } } } } } } } ```