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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?..."
]
}

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:

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.