Keywords: korean business reviews, naver map reviews, naver place, south korea reviews, south korea, korean web scraping, naver data, apify actor, korean data extraction

Naver Place Review Scraper 🇰🇷

Scrape visitor reviews, ratings, and statistics from Naver Place (네이버 플레이스) — Korea's largest local business platform.

🚀 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 — 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 — no full URL needed.

✨ Features

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

🎯 Use Cases

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

📊 Output Fields

Review Object

Field	Type	Description
reviewId	string	Unique Naver review identifier
body	string	Full review text written by the visitor
rating	integer	Star rating from 1 (worst) to 5 (best)
authorNickname	string	Reviewer's public display name
visited	string	Date the reviewer visited the business
created	string	Date/time the review was posted
visitCount	integer	How many times this reviewer has visited this place
votedKeywords	array	Keywords other users voted as accurate (e.g., "분위기가 좋아요", "음식이 맛있어요")
mediaUrls	array	URLs of photos/videos attached to the review
mediaCount	integer	Total number of media attachments
businessName	string	Name of the business being reviewed
placeId	string	Naver Place ID for the business

Statistics Object

Field	Type	Description
totalReviews	integer	Total number of visitor reviews for this place
avgRating	float	Average star rating (1.0–5.0)
themes	array	Review themes with occurrence counts (e.g., "가성비가 좋은")
topMenus	array	Most frequently mentioned menu items with counts
votedKeywords	object	Distribution of keyword votes across all reviews

⚙️ Input Parameters

Parameter	Type	Default	Description
placeUrls	array	—	List of Naver Place URLs to scrape
placeId	string	—	Single Place ID (alternative to URLs)
maxReviews	integer	100	Max reviews per place (1–1,000)
sortBy	string	"recent"	Sort order: "recent" (최신순) or "qualityScore" (리뷰도움순)
includeStats	boolean	true	Include aggregate review statistics
proxyConfiguration	object	—	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"]
    }
}

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

🛡️ Proxy Recommendations

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

🔧 Technical Details

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

💰 Pricing

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

🔗 Related Actors — Naver Place Suite

• Naver Place Search — Search places by keyword, get 25+ fields per listing
• Naver Place Blog Review Scraper — Blog/cafe reviews with full text
• Naver Place Photo Scraper — Business & visitor photos
• Naver Blog Search Scraper — Search Naver blogs by keyword

⚠️ 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.