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Hostelworld Reviews Scraper

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from $2.00 / 1,000 results

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Hostelworld Reviews Scraper

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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4 days ago

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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?..."
]
}
FieldTypeDescription
urlsarrayHotel 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_urlintegerMaximum number of reviews to collect per URL. Default: 20. Set higher (e.g., 200) to capture more reviews per property.
ignore_url_failuresbooleanIf 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 urls array. 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:

FieldMeaning
SummaryShort headline or title of the review, as written by the guest (e.g., "Great location, small rooms")
Date SubmittedThe date the review was posted on Hostelworld
ScoreNumerical rating given by the reviewer, typically on a 1–10 scale
ReviewerName or identifier of the guest who submitted the review
TextFull body of the review — the detailed written feedback from the traveler

How to Use

  1. Get hotel URLs — Open any hotel detail page on Hostelworld (e.g., tpi.hostelworld.com/hotels/...) and copy the full URL, including query parameters.
  2. Configure input — Paste URLs into the urls array. Set max_items_per_url to control how many reviews to fetch per property.
  3. Set fault tolerance — Keep ignore_url_failures: true for bulk runs to avoid interruptions from occasional failed requests.
  4. Run the scraper — Start the actor and monitor progress in the run log.
  5. 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_url limit — 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.