How to Scrape TripAdvisor Reviews and Ratings

TripAdvisor is a goldmine of travel data with millions of reviews for hotels, restaurants, and attractions. Scraping this data enables sentiment analysis, price comparison, and travel market research.

Challenges

TripAdvisor's protections include:

• Cloudflare-based bot detection
• Rate limiting and IP blocking
• Lazy-loaded review content
• Pagination requiring interaction

Scraping TripAdvisor with ScraperAPI

import requests
from bs4 import BeautifulSoup
import time

API_KEY = "YOUR_SCRAPERAPI_KEY"

def scrape_tripadvisor_hotel(hotel_url, review_pages=3):
    hotel_data = {"reviews": []}

    # Get hotel overview
    response = requests.get("https://api.scraperapi.com", params={
        "api_key": API_KEY,
        "url": hotel_url,
        "render": "true"
    })

    soup = BeautifulSoup(response.text, "html.parser")

    name = soup.select_one('[data-test-target="top-info-header"]')
    rating = soup.select_one('[class*="overallRating"]')

    hotel_data["name"] = name.text.strip() if name else "N/A"
    hotel_data["rating"] = rating.text.strip() if rating else "N/A"

    # Scrape reviews across pages
    for page in range(review_pages):
        offset = page * 10
        review_url = hotel_url.replace("-Reviews-", f"-Reviews-or{offset}-")

        response = requests.get("https://api.scraperapi.com", params={
            "api_key": API_KEY,
            "url": review_url,
            "render": "true"
        })

        soup = BeautifulSoup(response.text, "html.parser")
        reviews = soup.select('[data-test-target="reviews-tab"] [class*="review-container"]')

        for review in reviews:
            title_el = review.select_one('[data-test-target="review-title"]')
            text_el = review.select_one('[class*="reviewText"]')
            bubble = review.select_one('[class*="bubble_rating"]')

            hotel_data["reviews"].append({
                "title": title_el.text.strip() if title_el else "N/A",
                "text": text_el.text.strip() if text_el else "N/A",
                "rating": bubble.get("class", [""])[1] if bubble else "N/A"
            })

        time.sleep(3)

    return hotel_data

hotel = scrape_tripadvisor_hotel(
    "https://www.tripadvisor.com/Hotel_Review-g60763-d93437-Reviews-Hotel_Example-New_York.html"
)
print(f"{hotel['name']} - Rating: {hotel['rating']}")
print(f"Scraped {len(hotel['reviews'])} reviews")

Scraping Restaurant Data

def scrape_tripadvisor_restaurants(location_url):
    response = requests.get("https://api.scrapingant.com/v2/general", params={
        "x-api-key": "YOUR_SCRAPINGANT_KEY",
        "url": location_url,
        "browser": "true",
        "proxy_type": "residential"
    })

    html = response.json()["content"]
    soup = BeautifulSoup(html, "html.parser")

    restaurants = []
    for card in soup.select('[data-test*="restaurant"]'):
        name = card.select_one("a[class*='name']")
        rating = card.select_one('[class*="rating"]')
        cuisine = card.select_one('[class*="cuisine"]')

        if name:
            restaurants.append({
                "name": name.text.strip(),
                "rating": rating.text.strip() if rating else "N/A",
                "cuisine": cuisine.text.strip() if cuisine else "N/A"
            })

    return restaurants

Data You Can Extract

• Hotel/restaurant name, address, and contact info
• Overall rating and individual review scores
• Review text, title, date, and reviewer info
• Price range and amenities
• Photos and room types
• Ranking within destination

Best Practices

1. Use residential proxies, TripAdvisor blocks datacenter IPs aggressively
2. Enable JavaScript rendering, reviews are dynamically loaded
3. Add 3-5 second delays between requests
4. Handle Cloudflare challenges via ScraperAPI or ScrapingAnt
5. Monitor for HTML changes, TripAdvisor updates its structure frequently

Verdict

TripAdvisor scraping requires robust anti-bot handling. ScraperAPI with residential proxies and JavaScript rendering delivers the most consistent results. ScrapingAnt's headless Chrome approach is equally effective. Both are strongly recommended over attempting raw proxy rotation yourself.