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Naver Place Reviews

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Pay per usage

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Naver Place Reviews

Naver Place Reviews

Scrape visitor reviews, ratings, and statistics from Naver Place (넀이버 ν”Œλ ˆμ΄μŠ€) β€” Korea's #1 local business platform. Extract review text, author info, voted keywords, popular menus, themes, and media URLs. Fast GraphQL-based extraction with no browser needed.

Pricing

Pay per usage

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Developer

Session zero

Session zero

Maintained by Community

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0

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2

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1

Monthly active users

20 hours ago

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Naver Place Review Scraper πŸ‡°πŸ‡·

Scrape visitor reviews, ratings, and statistics from Naver Place (넀이버 ν”Œλ ˆμ΄μŠ€) β€” Korea's largest local business platform.

πŸš€ Quick Start (3 minutes)

  1. Click "Try for free" on the Actor page
  2. Paste a Naver Place URL into placeUrls:
    {
    "placeUrls": [
    { "url": "https://pcmap.place.naver.com/restaurant/1085956231/review/visitor" }
    ],
    "maxReviews": 50
    }
  3. Click Start β€” reviews appear in the Dataset tab within seconds
  4. Export as JSON, CSV, or Excel

Tip: You can also just enter a Place ID like 1085956231 β€” no full URL needed.

✨ Features

  • Fast & Efficient β€” No browser needed. Uses direct API calls (Apollo State + GraphQL)
  • Comprehensive Data β€” Review text, ratings, author info, visit details, media, voted keywords
  • Review Statistics β€” Aggregate stats: themes, popular menus, keyword analysis
  • Sort Options β€” Sort by newest (μ΅œμ‹ μˆœ) or most helpful (λ¦¬λ·°λ„μ›€μˆœ)
  • Batch Scraping β€” Process multiple places in a single run
  • Proxy Support β€” Built-in Apify Proxy integration to avoid IP blocks
  • Automatic Retry β€” Exponential backoff on network/server errors for reliability

🎯 Use Cases

  • Competitive Analysis β€” Compare review scores and keyword sentiment across competing restaurants or shops
  • Brand Monitoring β€” Track new reviews mentioning your business in real time
  • Menu Optimization β€” Identify which menu items get praised or criticized using voted keywords and top menu data
  • Location Intelligence β€” Evaluate customer satisfaction before opening a new branch nearby
  • Sentiment & NLP Research β€” Feed Korean review text into sentiment analysis or topic modeling pipelines
  • Market Research β€” Aggregate review trends across a category (e.g., all cafΓ©s in Gangnam)

πŸ“Š Output Fields

Review Object

FieldTypeDescription
reviewIdstringUnique Naver review identifier
bodystringFull review text written by the visitor
ratingintegerStar rating from 1 (worst) to 5 (best)
authorNicknamestringReviewer's public display name
visitedstringDate the reviewer visited the business
createdstringDate/time the review was posted
visitCountintegerHow many times this reviewer has visited this place
votedKeywordsarrayKeywords other users voted as accurate (e.g., "λΆ„μœ„κΈ°κ°€ μ’‹μ•„μš”", "μŒμ‹μ΄ λ§›μžˆμ–΄μš”")
mediaUrlsarrayURLs of photos/videos attached to the review
mediaCountintegerTotal number of media attachments
businessNamestringName of the business being reviewed
placeIdstringNaver Place ID for the business

Statistics Object

FieldTypeDescription
totalReviewsintegerTotal number of visitor reviews for this place
avgRatingfloatAverage star rating (1.0–5.0)
themesarrayReview themes with occurrence counts (e.g., "κ°€μ„±λΉ„κ°€ 쒋은")
topMenusarrayMost frequently mentioned menu items with counts
votedKeywordsobjectDistribution of keyword votes across all reviews

βš™οΈ Input Parameters

ParameterTypeDefaultDescription
placeUrlsarrayβ€”List of Naver Place URLs to scrape
placeIdstringβ€”Single Place ID (alternative to URLs)
maxReviewsinteger100Max reviews per place (1–1,000)
sortBystring"recent"Sort order: "recent" (μ΅œμ‹ μˆœ) or "qualityScore" (λ¦¬λ·°λ„μ›€μˆœ)
includeStatsbooleantrueInclude aggregate review statistics
proxyConfigurationobjectβ€”Apify Proxy settings (recommended for high volume)

Example Input

{
"placeUrls": [
{ "url": "https://pcmap.place.naver.com/restaurant/1085956231/review/visitor" }
],
"maxReviews": 200,
"sortBy": "recent",
"includeStats": true,
"proxyConfiguration": {
"useApifyProxy": true,
"apifyProxyGroups": ["SHADER"]
}
}

πŸ”— Supported URL Formats

  • https://pcmap.place.naver.com/restaurant/1085956231/review/visitor
  • https://m.place.naver.com/restaurant/1085956231
  • https://map.naver.com/p/entry/place/1085956231
  • Just the numeric ID: 1085956231

⚠️ Limitations & Notes

  • Max 1,000 reviews per place β€” configurable via maxReviews (default 100)
  • Rate limiting β€” Naver may throttle requests at high volume; use proxy and keep runs reasonable
  • Retry logic β€” Automatic retry with exponential backoff (2s β†’ 4s β†’ 8s) on 429/5xx errors, up to 3 retries
  • Page size β€” API returns 20 reviews per page; large runs require multiple paginated requests
  • Data freshness β€” Reviews are scraped in real time; results reflect the current state of the listing
  • No login required β€” All data is publicly accessible

πŸ›‘οΈ Proxy Recommendations

VolumeRecommendation
Low (< 50 reviews)No proxy needed
Medium (50–500 reviews)Datacenter proxy (SHADER group)
High (500+ reviews)Residential proxy recommended

πŸ”§ Technical Details

  1. HTML Fetch β€” Loads the place review page and extracts Apollo State (SSR data) for statistics
  2. GraphQL Pagination β€” Uses Naver's internal GraphQL API with cursor-based pagination for reviews
  3. Retry Logic β€” Automatic retry with exponential backoff on network/server errors
  4. Proxy Integration β€” Routes all requests through Apify Proxy when configured

πŸ’° Pricing

$0.50 per 1,000 reviews β€” pay only for what you scrape. Platform usage (Actor start) is included at minimal cost.

⚠️ Disclaimer

This Actor is provided for educational and research purposes. Please respect Naver's Terms of Service and use responsibly. The author is not responsible for any misuse of this tool.