Naver Blog Scraper — Search + Post Content + Cafe [$1.5💰]

Naver Blog Scraper — Blog Search + Post Content + Cafe Articles

Turn Naver Blog and public Naver Cafes into structured data. Paste a keyword to search Naver's blog index, a blog.naver.com post URL to pull the full Korean post body, or a cafe ID to list a public cafe's articles — every query line is auto-classified, and every row is flat, UTF-8-clean JSON.

Why Use This Scraper?

• ✅ Three sources in one actor — blog keyword search, full post content, public cafe articles
• ✅ Paste keywords, post URLs, or cafe IDs together — each line auto-routed
• ✅ Optional post-body enrichment — attach full text, images, and tags to every search hit
• ✅ Optional comments — every comment on each post or cafe article, with author, time, and reply flag
• ✅ Korean-safe UTF-8 output end to end — no mojibake in titles, bodies, or nicknames
• ✅ Date-range filters and relevance / recency sorting for search
• ✅ No login or API key needed — fast runs, and proxies are optional

Overview

The Naver Blog Scraper is built for marketing and influencer agencies, brand-monitoring teams, SEO specialists, and researchers who need structured data out of Korea's dominant blogging and community platform.

The output is a stream of flat rows carrying a type discriminator: a keyword yields searchResult rows, a post URL yields one post row with the full body, and a cafe ID yields cafeArticle rows. Every row echoes the originating query, so mixed runs stay trivial to split downstream. Turn on includePostContent and each search result is upgraded in place with the post's body text, images, and tags. Turn on includeComments and each post or article is followed by its comment rows, linked back by postUrl.

Supported Inputs

Query types (auto-detected per line)

Query type	Pattern	Example	Rows produced
Blog keyword search	free text (any language)	맛집 or seoul cafe	one searchResult row per matching post
Full post content	blog.naver.com / m.blog.naver.com URL	https://blog.naver.com/someblog/223340163450	one post row with the full body
Public cafe articles	cafeId:{clubId} or cafe URL	cafeId:10322296 or https://cafe.naver.com/joonggonara	one cafeArticle row per article

Copy-pasteable input

{
  "queries": [
    "맛집",
    "https://blog.naver.com/someblog/223340163450",
    "cafeId:10322296"
  ],
  "maxItems": 200
}

Unsupported inputs

• ❌ Members-only / private cafe boards (only public cafe articles are returned)
• ❌ Naver Shopping, Maps, or Place data — for Place reviews use Naver Place Review Scraper
• ❌ Content behind a Naver login, and posts the author has set to private

Use Cases

Audience	Use case
Influencer / blog-marketing agencies	Find relevant bloggers, verify sponsored posts went live, measure reach, track competitor campaigns
Brand & reputation teams	Monitor what Korean bloggers say about a brand; catch negative reviews early
SEO / content teams	Reverse-engineer what ranks in Naver search; keyword and content-gap research
Market researchers	Aggregate blog mentions of a product or topic for trend and sentiment analysis
Community analysts	Track discussion volume and topics across public Naver Cafes

How It Works

1. Input — add any mix of keywords, post URLs, and cafe IDs, one per line
2. Classify — each line is auto-routed: a keyword runs a blog search, a post URL returns that post, a cafe ID returns that cafe's articles
3. Fetch — public blog and cafe data is collected with parallel requests and automatic retries, so a temporary error never costs you a row
4. Enrich (optional) — with includePostContent, each search result also returns its full body text, images, and tags
5. Output — flat, typed, UTF-8 JSON rows land in the dataset, exportable as JSON, CSV, Excel, or XML

Input Configuration

Input fields

Field	Type	Required	Notes
queries	array<string>	yes	One query per line; each auto-classified (see Supported Inputs)
includePostContent	boolean	optional	Enrich each search result with full body text, images, tags. Roughly doubles requests. Default false
includeComments	boolean	optional	Add each post's or article's comments as comment rows. $0.03 per post whose comments come back, plus the per-row price. Default false. Available from 2026-11-23
maxCommentsPerPost	integer	optional	Most comment rows kept per post (1-1000). Default 50
orderBy	string enum	optional	Search sort: sim (relevance) or recentdate (newest). Default sim
from	string (date)	optional	Search mode only: results published on/after YYYY-MM-DD
to	string (date)	optional	Search mode only: results published on/before YYYY-MM-DD; empty = up to now
maxItems	integer	optional	Global cap on rows across all queries. Default 100
maxConcurrency	integer	optional	Parallel requests, default 3, hard cap 10. Lower it if runs slow down or fail
proxy	object	optional	Off by default. Residential proxies recommended; the default works out of the box

Common scenarios

1. Blog search, newest first, enriched with full post bodies

{
  "queries": ["강남 카페"],
  "includePostContent": true,
  "orderBy": "recentdate",
  "maxItems": 50
}

2. Date-sliced harvest (get past Naver's ~1,000-result cap)

{
  "queries": ["신제품 리뷰"],
  "orderBy": "recentdate",
  "from": "2026-01-01",
  "to": "2026-03-31",
  "maxItems": 1000
}

3. Public cafe article list

{
  "queries": ["cafeId:10322296"],
  "maxItems": 300
}

Output Overview

Every row is flat and carries type, query, and scrapedAt, plus:

• searchResult rows — post URL, title, snippet, blogId, logNo, author nickname, blog name, publish date, thumbnail URLs, and totalCount for the query. With includePostContent, also bodyText, bodyImageUrls, and tags.
• post rows — post URL, blogId, logNo, title, author, publish date, full bodyText, bodyImageUrls, and tags.
• cafeArticle rows — cafe ID and name, article ID and URL, subject, board (menu) name, writer nickname, read/comment/like counts, write date, and whether the article has images.
• comment rows (with includeComments) — the post or article URL, comment author, text, time (ISO), and whether it is a reply. maxItems caps posts and articles; comments come on top.

Output Samples

Keyword query → searchResult row (trimmed)

{
  "type": "searchResult",
  "query": "카페",
  "postUrl": "https://blog.naver.com/hope95_08_30/224343354021",
  "title": "구로디지털단지 카페드루와ㅣ가성비카페 내돈내산 솔직후기",
  "snippet": "구로디지털단지 가성비카페 카페드루와 … 오늘 소개해 드릴 곳은 …",
  "blogId": "hope95_08_30",
  "logNo": "224343354021",
  "authorName": "찌니",
  "blogName": "찌니와 동이의 일상",
  "blogUrl": "https://blog.naver.com/hope95_08_30",
  "postDate": "2026-07-12T00:00:00.000Z",
  "thumbnailUrls": ["https://blogthumb.pstatic.net/…"],
  "totalCount": 1000,
  "scrapedAt": "2026-07-17T…"
  /* + bodyText, bodyImageUrls, tags when includePostContent is on */
}

Post URL query → post row (trimmed)

{
  "type": "post",
  "query": "https://blog.naver.com/yeewon1217/223340163450",
  "postUrl": "https://blog.naver.com/yeewon1217/223340163450",
  "mobilePostUrl": "https://m.blog.naver.com/yeewon1217/223340163450",
  "blogId": "yeewon1217",
  "logNo": "223340163450",
  "title": "2024년 1월 이야기",
  "authorName": "에온",
  "publishedAt": "2024-01-…",
  "bodyText": "…1,518 characters of Korean post body…",
  "bodyImageUrls": ["https://postfiles.pstatic.net/…", "… 71 images …"],
  "tags": []
}

Cafe query → cafeArticle row

{
  "type": "cafeArticle",
  "query": "cafeId:10322296",
  "cafeId": "10322296",
  "cafeName": "ㆍ피터팬의 좋은방 구하기ㆍ",
  "articleId": "19570814",
  "articleUrl": "https://cafe.naver.com/ca-fe/cafes/10322296/articles/19570814",
  "subject": "거주후기",
  "menuName": "거주 후기",
  "writerNickname": "오오육아라",
  "maskedMemberId": "chae****",
  "readCount": 0,
  "commentCount": 0,
  "likeCount": 0,
  "hasImage": false,
  "scrapedAt": "2026-07-17T…"
}

Comments on → comment row

{
  "type": "comment",
  "query": "https://blog.naver.com/cane1/224463486429",
  "postUrl": "https://blog.naver.com/cane1/224463486429",
  "commentAuthor": "한라봉봉",
  "commentText": "글 잘 읽었어용! 사진도 너무 예쁘고 글도 알차서 재밌게 봤습니당~",
  "commentedAt": "2026-11-08T14:24:07.000Z",
  "isReply": false,
  "scrapedAt": "2026-11-08T…"
}

Key Output Fields

Common

• type, query, scrapedAt

Blog search result

• postUrl, title, snippet, blogId, logNo, gdid
• authorName, blogName, blogUrl, postDate, thumbnailUrls, totalCount

Blog post

• title, authorName, publishedAt, bodyText
• bodyImageUrls, tags, mobilePostUrl

Cafe article

• cafeId, cafeName, articleId, articleUrl, subject, menuName
• writerNickname, maskedMemberId, readCount, commentCount, likeCount, writeDate, hasImage

Comment

• postUrl, commentAuthor, commentText, commentedAt, isReply

FAQ

Do I need a proxy?

Usually not — it works without one from most IPs, and retries handle the occasional failed request automatically. For high-volume runs, residential proxies are recommended; enable them in the proxy input.

How does the actor decide which mode to run?

By the shape of each query line: a blog.naver.com/m.blog.naver.com URL fetches full post content, cafeId: or a cafe.naver.com URL lists cafe articles, and anything else is a blog keyword search. Mix all three in one run.

Why do I only get about 1,000 results for a popular keyword?

Naver caps every blog search query at roughly 1,000 reachable results. To harvest more, sort by recentdate and split the run into from/to date ranges — each slice returns its own up-to-1,000 window.

What does includePostContent cost me?

It fetches each search result's full post as well, which roughly doubles the number of requests per run. Keep maxItems modest when it's on, and expect longer runtimes.

What do comments cost?

$0.03 for each post or cafe article whose comments come back, plus the normal price for every comment row. A post with no comments costs nothing extra, and a post found by two of your queries is looked up once. maxCommentsPerPost trims how many comments you keep (the per-post charge stays the same). Comments are available from 2026-11-23; a run that asks for them earlier skips them and says so in the log.

Can I scrape private or members-only content?

No. The actor reads only public blog posts and public cafe articles. Members-only cafe boards, private posts, and anything behind a Naver login are out of scope.

Does it handle Korean text correctly?

Yes — the entire pipeline is UTF-8, so Korean titles, post bodies, tags, and cafe nicknames come through intact with no mojibake.

Does this scrape Naver Shopping, Maps, or Place reviews?

Not this actor. For visitor reviews, ratings and blog posts about a restaurant, shop or clinic on Naver Map, use Naver Place Review Scraper. Naver Shopping is not covered.

Support

• For issues or feature requests, please use the Issues tab on the actor's Apify Console page.
• Author's website: https://muhamed-didovic.github.io/
• Email: muhamed.didovic@gmail.com

Additional Services

• Need Naver Place / Maps / Shopping coverage, comment threads, or scheduled monitoring? Those are bigger builds — drop a line and I'll scope them.
• Custom output shapes, private builds, or direct API access (no Apify fee, just a usage fee): muhamed.didovic@gmail.com

Explore More Scrapers

If you found this useful, you might also like:

• Internet Archive Scraper — Wayback snapshots, library search, and item metadata
• Trustpilot Scraper — company reviews at scale
• VRBO Scraper — vacation rentals with calendar, rates, and full reviews

Full list at apify.com/memo23.

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🤖 For AI Agents & LLM Apps

Compact reference for AI agents calling this actor via the Apify MCP server or the Apify API (actor: memo23/naver-blog-scraper).

Purpose: Scrape Naver Blog and public Naver Cafes — each query line is auto-classified into a blog keyword search, a full post-content fetch, or a public cafe article list, emitting flat UTF-8 rows.

Minimal input:

{
  "queries": ["맛집"],
  "includePostContent": false,
  "orderBy": "sim",
  "maxItems": 50,
  "maxConcurrency": 3,
  "proxy": { "useApifyProxy": false }
}

queries also accepts post URLs (https://blog.naver.com/{blogId}/{logNo}) and cafe IDs (cafeId:10322296 or a cafe.naver.com URL). Optional from / to (YYYY-MM-DD) filter search-mode results by publish date.

Output: every row carries type, query, scrapedAt. searchResult rows add postUrl, title, snippet, blogId, logNo, gdid, authorName, blogName, blogUrl, postDate, thumbnailUrls, totalCount. post rows add title, authorName, publishedAt, bodyText, bodyImageUrls, tags, mobilePostUrl. cafeArticle rows add cafeId, cafeName, articleId, articleUrl, subject, menuName, writerNickname, maskedMemberId, readCount, commentCount, likeCount, writeDate, hasImage. comment rows add postUrl, commentAuthor, commentText, commentedAt, isReply.

Behaviors an agent should know:

• queries mixes all three types in one run; each line is routed by its shape.
• Always set maxItems (default 100). Naver caps each blog search at ~1,000 reachable results — sort recentdate and slice from/to date ranges to harvest more.
• includePostContent enriches search results with body/images/tags but roughly doubles request count.
• includeComments (off by default, from 2026-11-23) adds comment rows (postUrl, commentAuthor, commentText, commentedAt, isReply) after each post or article; billed $0.03 per post whose comments come back plus the per-row price. maxCommentsPerPost (default 50) trims them; they do not count toward maxItems.
• Keep maxConcurrency low (hard cap 10); lower it if runs slow down or fail. Proxy is off by default; residential proxies are recommended for high-volume runs.
• Pay-per-event billing — see the Pricing tab on the actor page.

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⚠️ Disclaimer

This Actor is an independent tool and is not affiliated with, endorsed by, or sponsored by NAVER Corporation or any of its subsidiaries. All trademarks mentioned are the property of their respective owners.

The scraper accesses only publicly available data on blog.naver.com and public Naver Cafe boards — no authenticated endpoints, no members-only boards, and no content behind the Naver login. Users are responsible for ensuring their use complies with NAVER's Terms of Service, applicable data-protection law (South Korea's PIPA, GDPR, CCPA, etc.), and any contractual obligations of their own organization. Please keep concurrency low to respect Naver's infrastructure.

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