Hostelworld Reviews Scraper
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from $2.00 / 1,000 results
Hostelworld Reviews Scraper
Collect guest reviews from Hostelworld.com hotel pages in bulk. This scraper extracts review summaries, scores, dates, reviewer info, and full text — perfect for sentiment analysis, reputation monitoring, and travel research.
Pricing
from $2.00 / 1,000 results
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Hostelworld.com Reviews Scraper: Extract Hotel Reviews at Scale
What Is Hostelworld.com?
Hostelworld is a global travel booking platform specializing in hostels, hotels, and budget accommodation. Beyond listings, it hosts a large volume of verified guest reviews that reflect real traveler experiences. Manually reading and compiling these reviews is impractical at scale — the Hostelworld Reviews Scraper automates extraction, turning review pages into structured datasets ready for analysis.
Overview
The Hostelworld Reviews Scraper targets hotel detail pages on Hostelworld's platform and collects all available guest reviews per property. It is built for:
- Hotel managers monitoring guest sentiment and reputation
- Travel researchers studying accommodation trends and traveler behavior
- Data analysts building datasets for NLP or sentiment analysis pipelines
- Aggregator developers enriching property listings with review data
The scraper supports bulk URL input, configurable item limits, and fault-tolerant execution — skipping failed URLs without stopping the entire run.
Input Format
{"ignore_url_failures": true,"max_items_per_url": 200,"urls": ["https://www.tpi.hostelworld.com/hotels/28045748/APA-Hotel-Resort-Ryogoku-Ekimae-Tower?..."]}
| Field | Type | Description |
|---|---|---|
urls | array | Hotel detail page URLs from Hostelworld. Add one per line or use Bulk Edit. Each URL should point to a specific property's detail page (e.g., tpi.hostelworld.com/hotels/...). |
max_items_per_url | integer | Maximum number of reviews to collect per URL. Default: 20. Set higher (e.g., 200) to capture more reviews per property. |
ignore_url_failures | boolean | If true, the scraper continues running when a URL fails instead of halting the entire run. Recommended for bulk jobs. Default: true. |
Tip: To scrape reviews for multiple properties, add each hotel's detail URL to the
urlsarray. The full URL including query parameters (?q=...) is supported and recommended for accurate results.
Output Format
Example record:
{"summary": "Nice place to stay","date_submitted": "2026-05-21T00:00:00","score": "8.0","reviewer": {"country": "AR","name": "Ana","travel_purpose": "leisure","type": "solo"},"text": ["Clean","Small rooms"]}
Each review record contains 5 fields:
| Field | Meaning |
|---|---|
Summary | Short headline or title of the review, as written by the guest (e.g., "Great location, small rooms") |
Date Submitted | The date the review was posted on Hostelworld |
Score | Numerical rating given by the reviewer, typically on a 1–10 scale |
Reviewer | Name or identifier of the guest who submitted the review |
Text | Full body of the review — the detailed written feedback from the traveler |
How to Use
- Get hotel URLs — Open any hotel detail page on Hostelworld (e.g.,
tpi.hostelworld.com/hotels/...) and copy the full URL, including query parameters. - Configure input — Paste URLs into the
urlsarray. Setmax_items_per_urlto control how many reviews to fetch per property. - Set fault tolerance — Keep
ignore_url_failures: truefor bulk runs to avoid interruptions from occasional failed requests. - Run the scraper — Start the actor and monitor progress in the run log.
- Export data — Download results as JSON, CSV, or Excel for use in analytics tools or dashboards.
Common issues:
- If no reviews are returned, verify the URL points to a hotel detail page, not a search results or listing page.
- Some properties may have fewer reviews than the
max_items_per_urllimit — this is expected behavior.
Use Cases & Business Value
- Reputation monitoring: Track guest sentiment for your property or competitors over time
- Sentiment analysis: Feed review text into NLP models to identify common complaints or praise
- Market research: Understand traveler expectations in specific cities or property categories
- Content enrichment: Supplement hotel listings with authentic guest feedback
The Hostelworld Reviews Scraper turns hundreds of individual review pages into a clean, queryable dataset — saving hours of manual work and enabling insights at a scale impossible through manual browsing.
Conclusion
Whether you're a hotel operator tracking your reputation, a researcher studying traveler behavior, or a developer building a review aggregator, the Hostelworld Reviews Scraper delivers structured review data quickly and reliably. Start collecting today and turn guest feedback into actionable intelligence.