{
  "data": {
    "id": "9JtqHelNzhr3DlUjU",
    "userId": "HIMU0xktu1JeZb4Xl",
    "name": "airbnb-reviews-scraper",
    "username": "fetch_cat",
    "description": "Extract public Airbnb reviews, reviewer details, ratings, dates, host responses, and listing context from room URLs for STR research.",
    "isPublic": true,
    "createdAt": "2026-06-26T19:37:25.449Z",
    "modifiedAt": "2026-07-17T01:22:53.818Z",
    "taggedBuilds": {
      "latest": {
        "buildId": "CiNWgsmJKX3gXoc5l",
        "finishedAt": "2026-07-17T01:22:53.818Z",
        "buildNumberInt": 100011,
        "buildNumber": "0.1.11"
      }
    },
    "stats": {
      "totalBuilds": 11,
      "totalRuns": 81,
      "totalUsers": 3,
      "totalUsers7Days": 1,
      "totalUsers30Days": 2,
      "totalUsers90Days": 2,
      "lastRunStartedAt": "2026-08-26T15:34:41.870Z",
      "actorReviewCount": 0,
      "actorReviewRating": 0,
      "bookmarkCount": 0,
      "publicActorRunStats30Days": {
        "ABORTED": 0,
        "FAILED": 0,
        "SUCCEEDED": 30,
        "TIMED-OUT": 0,
        "TOTAL": 30
      }
    },
    "versions": [
      {
        "versionNumber": "0.1",
        "sourceType": "SOURCE_FILES",
        "buildTag": "latest"
      }
    ],
    "defaultRunOptions": {
      "build": "latest",
      "timeoutSecs": 300,
      "memoryMbytes": 512
    },
    "exampleRunInput": {
      "body": "{\"startUrls\": [{\"url\": \"https://www.airbnb.com/rooms/20669368\"}], \"maxReviewsPerListing\": 10, \"sort\": \"recent\", \"proxyConfiguration\": {\"useApifyProxy\": false}}",
      "contentType": "application/json; charset=utf-8"
    },
    "categories": [
      "TRAVEL",
      "REAL_ESTATE",
      "AUTOMATION"
    ],
    "isDeprecated": false,
    "title": "Airbnb Reviews Scraper",
    "pictureUrl": "https://apify-image-uploads-prod.s3.us-east-1.amazonaws.com/HIMU0xktu1JeZb4Xl-actor-9JtqHelNzhr3DlUjU-1W6tePGg8r-airbnb-reviews-scraper.png",
    "seoTitle": "Airbnb Reviews Scraper: Extract Guest Review Data",
    "seoDescription": "Scrape public Airbnb reviews from listing URLs with guest text, dates, ratings, reviewer details, host replies, and listing context for analysis.",
    "pricingInfos": [
      {
        "pricingModel": "PAY_PER_EVENT",
        "startedAt": "2026-06-27T14:40:00.000Z",
        "pricingPerEvent": {
          "actorChargeEvents": {
            "start": {
              "eventTitle": "Run started",
              "eventDescription": "One-time fee charged when a run starts. Covers fixed startup cost.",
              "eventPriceUsd": 0.005,
              "isOneTimeEvent": true
            },
            "item": {
              "eventTitle": "Review saved",
              "eventDescription": "Charged per Airbnb review saved to the dataset.",
              "isPrimaryEvent": true,
              "eventPriceUsd": 0.000027604
            }
          }
        },
        "createdAt": "2026-06-27T14:27:08.088Z",
        "apifyMarginPercentage": 0.2
      }
    ],
    "notice": "NONE",
    "isCritical": false,
    "isGeneric": false,
    "hasNoDataset": false,
    "isSourceCodeHidden": true,
    "standbyUrl": null,
    "actorPermissionLevel": "LIMITED_PERMISSIONS",
    "readmeSummary": "## Airbnb Reviews Scraper\n\nAirbnb Reviews Scraper converts public Airbnb room/listing pages into structured review datasets by extracting guest review text, review timestamps, reviewer metadata (name, profile link, location), listing metadata (title, identifier, overall rating, total review count), per-review star ratings, language and translated text when available, host responses and response dates, and scrape timestamps. It processes one or more listing URLs per run and yields one record per review including listing context; supports limiting the number of reviews per listing, sorting by recency, and filtering by date range, rating range, or keyword. Unavailable attributes are preserved as null rather than fabricated. Outputs are suitable for sentiment analysis, topic classification, reputation monitoring, competitor research, and automated NLP/LLM pipelines.\n\n## Use cases\n\n- Property managers tracking guest sentiment across their managed listings.\n- Short-term rental analysts comparing competing stays within a destination.\n- Reputation teams monitoring recent public guest feedback.\n- Hospitality researchers building review datasets for market studies.\n- Automation teams feeding review text and metadata into BI, CRM, or AI workflows.\n- Recurring reputation monitoring (scheduled runs to capture new reviews and track changes).\n- Market research collecting reviews from competing listings to compare guest language, sentiment, and review frequency.\n- Guest experience analysis: export review text to NLP/LLM pipelines to classify recurring topics such as cleanliness, check-in, location, host communication, and amenities.",
    "deploymentKey": "ssh-rsa AAAAB3NzaC1yc2EAAAADAQABAAABAQDKB6a9VX7hNX8DVdOJfEGN++F1v2kdMEWku1rqykiW81rmWR8KhECLkdupHVNEVAldakVkGs16apM4dv6UXIgpvlJvxNqQKKiR7xv1yyNsTmypf11DZjzl2pW7aVPjEoTYBxwn7MsAHqDf1ii/+h/TkyQZTBVMtzNY3+wCIlU12WvzZXiU6SQAfdRvG5k1E+7M6r3/R8ZLh5IiGwAXpBzv4L1T+Nwm3Drj+0IWSwsFwa0fk0bLdK4QrDAf+R8kf6aepRGy0EQxG0UHJRMBVaHw01dMZXhhkx699KpqoWDv8Tyn2hKlGbhi5S9DdkzlBPn0qwUbjTUwANWPuBJpdsIP \n"
  }
}