Naver Blog Scraper - Clean Content & Review Intelligence

The only Naver Blog scraper that properly extracts clean content from Naver's iframe-based architecture.

Why This Actor?

Naver Blog loads post content inside an iframe, which means standard scrapers return raw page HTML filled with navigation menus, ads, and sidebar widgets. This Actor:

1. Detects the iframe and fetches the actual content page separately
2. Parses SmartEditor 2 and 3 (SE2/SE3) markup to extract structured text
3. Returns clean, readable content — no menus, no ads, no junk HTML

Other scrapers on the Apify Store charge $30/month and still can't solve the iframe problem. This one does it for free.

Key Features

1. Clean content extraction — Properly handles Naver's iframe + SmartEditor 2/3 architecture
2. Keyword search — Search Naver Blog by any Korean keyword
3. Direct URL input — Scrape specific blog post URLs directly
4. Sponsor detection — Automatically detects 협찬 (sponsored) vs 내돈내산 (organic) posts
5. Sponsored content filter — Show all, organic only, or sponsored only
6. Comment count — Extracted from listNumComment JS variable
7. Like count (공감) — Fetched via Naver's reaction API
8. Category extraction — Blog post category from categoryName JS variable
9. Tag/hashtag extraction — Parsed from tags JS array in inline scripts
10. Blog profile — Nickname, profile image, blog ID, visitor count
11. Date range filter — Filter keyword search results by publish date
12. HTML or text mode — Get clean text or original HTML markup
13. Auto deduplication — Skip duplicate posts by URL
14. Deleted/private post handling — Automatically skips unavailable posts
15. Run statistics — totalFound, uniqueCount, duplicatesRemoved, sponsoredSkipped

Output Fields

Field	Type	Example
title	string	"강남 맛집 추천 TOP 10"
url	string	"https://blog.naver.com/user/123"
author	string	"맛집탐험가"
date	string	"2024-01-15"
category	string	"맛집 리뷰"
content	string	Clean blog body text (or HTML)
tags	string[]	["강남맛집", "데이트코스"]
images	string[]	List of image URLs
commentCount	integer	12
likeCount	integer	45
isSponsored	boolean	false
sponsorType	string	"organic" / "sponsored" / "unknown"
blogProfile	object	{"nickname": "J베이지", "blogId": "jbeige_review", ...}

Quick Start

Search by keyword

{
    "keyword": "강남 맛집",
    "maxPosts": 20,
    "sort": "date",
    "sponsoredFilter": "organic_only"
}

Scrape specific URLs

{
    "startUrls": [
        { "url": "https://blog.naver.com/jbeige_review/224143632158" },
        { "url": "https://blog.naver.com/another_user/223456789012" }
    ]
}

Filter by date range

{
    "keyword": "제주도 여행",
    "maxPosts": 50,
    "dateStart": "2024-01-01",
    "dateEnd": "2024-06-30"
}

Get HTML content

{
    "keyword": "인테리어",
    "maxPosts": 10,
    "contentType": "html"
}

Use Cases

• Marketing analysis — Track brand mentions and sentiment across Naver Blog posts
• Competitor research — Monitor competitor product reviews and engagement metrics
• Review monitoring — Separate genuine reviews (내돈내산) from sponsored content (협찬) automatically
• NLP data collection — Collect clean Korean text data for training language models or sentiment analysis
• SEO research — Analyze top-ranking blog content for specific keywords
• Influencer discovery — Find bloggers with high engagement in your niche using comment/like counts and profile data

Input Options

Field	Type	Default	Description
startUrls	array	-	Direct blog post URLs to scrape
keyword	string	-	Korean keyword for Naver Blog search
maxPosts	integer	10	Max posts to scrape (1-500)
sort	string	"sim"	"sim" (relevance) or "date" (newest)
dateStart	string	-	Start date filter YYYY-MM-DD
dateEnd	string	-	End date filter YYYY-MM-DD
contentType	string	"text"	"text" or "html"
sponsoredFilter	string	"all"	"all", "organic_only", "sponsored_only"
deduplicate	boolean	true	Remove duplicate posts by URL

Integration Guide

Python: Export to Google Sheets

import gspread
from apify_client import ApifyClient

# 1. Run the scraper
client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("YOUR_ACTOR_ID").call(run_input={
    "keyword": "강남 맛집",
    "maxPosts": 50,
    "sponsoredFilter": "organic_only",
})

# 2. Get results
items = list(client.dataset(run["defaultDatasetId"]).iterate_items())

# 3. Write to Google Sheets
gc = gspread.service_account(filename="credentials.json")
sheet = gc.open("Naver Blog Data").sheet1

headers = ["title", "url", "author", "date", "category",
           "commentCount", "likeCount", "isSponsored", "sponsorType", "tags"]
sheet.update("A1", [headers])

rows = []
for item in items:
    rows.append([
        item.get("title", ""),
        item.get("url", ""),
        item.get("author", ""),
        item.get("date", ""),
        item.get("category", ""),
        item.get("commentCount", 0),
        item.get("likeCount", 0),
        item.get("isSponsored", False),
        item.get("sponsorType", ""),
        ", ".join(item.get("tags", [])),
    ])
sheet.update(f"A2:J{len(rows)+1}", rows)
print(f"Exported {len(rows)} rows to Google Sheets")

Prerequisites: pip install apify-client gspread, Google Cloud service account with Sheets API enabled.

n8n Workflow

1. Schedule Trigger — Set cron (e.g., every Monday 9 AM)
2. HTTP Request — POST to https://api.apify.com/v2/acts/YOUR_ACTOR_ID/runs?token=YOUR_TOKEN with input JSON body
3. Wait — Poll GET /v2/actor-runs/{runId} until status is SUCCEEDED
4. HTTP Request — GET https://api.apify.com/v2/datasets/{datasetId}/items?token=YOUR_TOKEN
5. Google Sheets — Append rows to your spreadsheet
6. Slack (optional) — Send summary notification

Make (Integromat) Workflow

1. Scheduler — Set interval
2. Apify: Run an Actor — Select Naver Blog Scraper, configure input
3. Apify: Get Dataset Items — Fetch results
4. Iterator — Loop through items
5. Google Sheets: Add a Row — Map fields to columns
6. Slack: Send a Message (optional) — Post summary

Apify Scheduling + Slack Webhook

1. Schedule: Apify Console → Actor → Schedules → Create schedule with cron (e.g., 0 9 * * 1)
2. Slack Webhook: Create Slack app → Enable Incoming Webhooks → Copy webhook URL
3. Connect: Apify Console → Actor → Integrations → Add webhook (Event: Actor run succeeded, URL: Slack webhook)
4. Payload:

   {
     "text": "Naver Blog Scraper completed!\nDataset: https://api.apify.com/v2/datasets/{{resource.defaultDatasetId}}/items?format=json"
   }