# Korean restaurant reputation scores and star distribution

**Use case:** 

Average rating, star distribution across 10 bands, reviewer counts and Naver's own theme analysis. Computed by Naver, no reviewer identity involved.

## Input

```json
{
  "queries": [
    "맛집"
  ],
  "regions": [
    "서울 강남구",
    "서울 마포구"
  ],
  "entityType": "businesses",
  "businessType": "restaurant",
  "maxResults": 200,
  "includeReputation": true,
  "maxReviewsPerBusiness": 50,
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}
```

## Output

```json
{
  "place_id": {
    "label": "Place id"
  },
  "name": {
    "label": "Name"
  },
  "category": {
    "label": "Category"
  },
  "region": {
    "label": "Region"
  },
  "visitor_review_count": {
    "label": "Visitor review count"
  },
  "blog_review_count": {
    "label": "Blog review count"
  },
  "reputation": {
    "label": "Reputation"
  },
  "place_url": {
    "label": "Place url"
  },
  "scraped_at": {
    "label": "Scraped at"
  },
  "from_cache": {
    "label": "From cache"
  },
  "fetched_at": {
    "label": "Fetched at"
  },
  "data_age_hours": {
    "label": "Data age hours"
  }
}
```

## About this Actor

This example demonstrates how to use [Naver Place Business & Reviews Scraper (Korea)](https://apify.com/oswaldocarabano/naver-place-scraper) with a specific input configuration. Visit the [Actor detail page](https://apify.com/oswaldocarabano/naver-place-scraper) to learn more, explore other use cases, and run it yourself.


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This Task's input is already configured above — use it as-is rather than inventing a new one.

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For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/oswaldocarabano/naver-place-scraper.md

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).