Airbnb Reviews Scraper — Ratings, Sentiment & Insights

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Export every guest review from any Airbnb listing — or an entire city — with full text, ratings, dates, reviewer details, host replies, photos, trip type, and language. Then go further than any other scraper: built-in sentiment, aspect tags, and a per-listing insights rollup (category sub-ratings, rating distribution, top keywords, review velocity, host-response rate). All in clean, stable JSON.

🏠 Part of the Airbnb suite — works alongside the Airbnb Search Scraper, Listing Details Scraper, and Revenue & Occupancy Calculator.

Why this one — more data, ~20% cheaper

~15 data dimensions vs the usual ~8 — for less money. Reliable by design (residential proxy + Airbnb's own reviews API, paginated).

Quick start

Pick any one input:

• City — type Austin, TX (we auto-find the top listings and scrape their reviews). No URLs required — unique to this actor.
• Listing URLs — paste https://www.airbnb.com/rooms/<id>.
• Listing IDs — paste numeric IDs.

Then set Max reviews per listing (0 = all), Sort (most recent / relevant / highest / lowest), optional Since date for incremental runs, and Start.

Input

Provide at least one of location, listingUrls, or listingIds.

Output

Two record types in one dataset (filter on recordType):

review — one per guest review: reviewId, rating, comment, localizedComment, language, date (ISO) + dateFormatted, reviewerName, reviewerLocation, reviewerTenure, reviewerPhotoUrl, hostReply, hostName, tripType, reviewHighlight, highlightedSentences[], media[], sentiment, sentimentScore, aspects[], listingId, listingUrl, scrapedAt.

listing_insights — one per listing (when includeInsights): totalReviewsAvailable, reviewsAnalyzed, avgRating, categoryRatings{cleanliness,accuracy,check-in,communication,location,value}, ratingDistribution{5..1}, sentimentSplitPct{positive,neutral,negative}, topPositiveKeywords[], topNegativeKeywords[], languagesBreakdown, hostResponseRatePct, reviewsPerMonth, firstReviewDate, lastReviewDate.

All fields always present (null/empty when unavailable). Full sample: docs/example-output-reviews.json.

Run via API

curl-X POST "https://api.apify.com/v2/acts/malikgen~airbnb-reviews-scraper/run-sync-get-dataset-items?token=YOUR_TOKEN"\
-H"Content-Type: application/json"\
-d'{"listingUrls":["https://www.airbnb.com/rooms/12937"],"maxReviewsPerListing":100}'

Works with the Apify clients, n8n, Make, and Zapier. Set webhookUrl to push results into your workflow.

Pricing

Pay per review (set in Console). Headline ≈ $3.30 / 1,000 reviews (Bronze) — about 20% under the market leader, with more fields. The per-listing insights rollup is included free.

FAQ

Can I really scrape a whole city? Yes — enter a city and we find the listings and pull their reviews automatically. No other Airbnb reviews scraper does this.

Do I need an API key for sentiment? No. Sentiment, scores, and aspect tags are computed in-actor at no extra cost.

How do incremental runs work? Set sortBy: most-recent + sinceDate — only newer reviews are returned. Pair with webhookUrl for ongoing reputation monitoring.

Why residential proxy? Airbnb is Cloudflare-protected and reviews load via a warmed session. Leave the default proxy on.

🏠 The Airbnb suite

Changelog

• 0.1 — Initial release. City / URL / ID input; paginated StaysPdpReviewsQuery; per-review sentiment + aspects; per-listing insights rollup (category ratings, distribution, sentiment split, keywords, velocity, response rate); reviewer location/tenure split; incremental sinceDate.

Not affiliated with, endorsed by, or sponsored by Airbnb. Scrapes publicly available review data for legitimate research, sentiment analysis, and reputation monitoring. Respect Airbnb's Terms of Service and applicable laws.