Naver Blog Comments Scraper (네이버 블로그 댓글)

Scrape all the comments and replies of Naver Blog posts. Paste post URLs and get one row per comment with the text, commenter name, commenter blog, date, likes, sticker and images. Each reply is linked to its parent comment, so you can rebuild every comment thread.

네이버 블로그 글의 댓글과 답글을 수집합니다. 로그인 없이 댓글 내용, 작성자, 작성자 블로그, 작성일, 공감 수, 스티커, 이미지를 JSON, CSV, Excel로 내려받으세요.

Export the comments as JSON, CSV, Excel, XML or HTML, or read them from the API. No Naver account. No login. No coding needed.

What does Naver Blog Comments Scraper do?

Give the scraper one or more Naver Blog post URLs. For each post, it returns all the public comments (댓글) and replies (답글), newest first:

• Comment data — the text (with line breaks), sticker, attached images, likes (공감), and the dates when the comment was written and edited.
• Commenter data — the commenter's name, their own Naver blog ID and URL, and their profile image.
• Thread data — isReply, parentCommentId and replyCount, so you can rebuild each conversation.
• Blog owner replies — isBlogOwner: true marks the comments and replies of the post's author.
• Post status report — a summary that tells you, for each post, if it had comments, had comments turned off, or was not found.
• Many posts in one run — add as many post URLs as you need. A post that you enter two times is scraped one time.

Use cases

• Customer and audience research — Read what readers say about a product, restaurant or brand under the most-read blog reviews.
• Influencer campaign tracking — Measure the comments that sponsored and influencer posts get, and how the blogger answers.
• Sentiment analysis — Collect clean Korean comment text for sentiment analysis, NLP, topic modeling or AI pipelines.
• Blogger and community discovery — Every commenter has a Naver blog, so you find the active bloggers in a niche.
• Engagement monitoring — Run the scraper on a schedule and collect the new comments on your own posts or your competitors' posts.

Input

Field	Type	Default	Description
postUrls	string[]	—	Naver Blog post URLs. Required
maxCommentsPerPost	integer	1000	The most comments (replies included) to return for each post, newest first. 0 = all the comments

These post URL forms all work:

• https://blog.naver.com/{blogId}/{logNo}
• https://m.blog.naver.com/{blogId}/{logNo}
• https://blog.naver.com/PostView.naver?blogId={blogId}&logNo={logNo}
• https://blog.naver.com/{blogId}?Redirect=Log&logNo={logNo}
• {blogId}/{logNo}, for example blogpeople/224425969565

Input examples

The newest 1,000 comments of one post

{
    "postUrls": ["https://blog.naver.com/blogpeople/224425969565"]
}

All the comments of two posts

{
    "postUrls": ["https://blog.naver.com/blogpeople/224425969565", "https://m.blog.naver.com/paperchan/224438187954"],
    "maxCommentsPerPost": 0
}

Only the newest 20 comments of each post — good for a daily schedule

{
    "postUrls": ["https://blog.naver.com/blogpeople/224425969565", "https://blog.naver.com/paperchan/224438187954"],
    "maxCommentsPerPost": 20
}

Output

You get one row for each comment or reply. Here is a comment and the blog owner's reply to it:

[
    {
        "postUrl": "https://blog.naver.com/paperchan/224438187954",
        "blogId": "paperchan",
        "logNo": "224438187954",
        "postTitle": "(청주) 극동반점",
        "commentId": "907345894548963539",
        "parentCommentId": null,
        "isReply": false,
        "replyCount": 1,
        "authorName": "부부식객관",
        "authorBlogId": "bubuohlak",
        "authorBlogUrl": "https://blog.naver.com/bubuohlak",
        "authorProfileImageUrl": "https://blogimgs.pstatic.net/imgs/emot/emo11.gif",
        "isBlogOwner": false,
        "text": "청주 극동반점의 옛날식 짜장면과 기본에 충실한 잡채라니 궁금하네요! 잡채 재료와 식감까지 자세히 써주셔서 잘 읽었어요 😊",
        "stickerUrl": null,
        "imageUrls": [],
        "likeCount": 0,
        "createdAt": "2026-10-11T11:01:55.000Z",
        "updatedAt": "2026-10-11T11:01:55.000Z",
        "scrapedAt": "2026-10-11T15:36:43.491Z"
    },
    {
        "postUrl": "https://blog.naver.com/paperchan/224438187954",
        "blogId": "paperchan",
        "logNo": "224438187954",
        "postTitle": "(청주) 극동반점",
        "commentId": "907346444237668468",
        "parentCommentId": "907345894548963539",
        "isReply": true,
        "replyCount": 0,
        "authorName": "레이니",
        "authorBlogId": "paperchan",
        "authorBlogUrl": "https://blog.naver.com/paperchan",
        "authorProfileImageUrl": "https://blogimgs.pstatic.net/item/personacon/11/38/1443811.gif",
        "isBlogOwner": true,
        "text": "^^",
        "stickerUrl": null,
        "imageUrls": [],
        "likeCount": 0,
        "createdAt": "2026-10-11T11:10:27.000Z",
        "updatedAt": "2026-10-11T11:10:27.000Z",
        "scrapedAt": "2026-10-11T15:36:43.485Z"
    }
]

Output fields

Field	Description
postUrl, blogId, logNo	The post that the comment belongs to
postTitle	The post title
commentId	Naver's ID of the comment
parentCommentId	For a reply: the commentId of the comment that it answers. null for a top-level comment
isReply	true for a reply (답글), false for a top-level comment
replyCount	The number of replies to a top-level comment. 0 for a reply
authorName	The commenter's display name
authorBlogId, authorBlogUrl	The commenter's own Naver blog
authorProfileImageUrl	The commenter's profile image
isBlogOwner	true when the post's author wrote the comment or reply
text	The comment text, with line breaks. null for a comment with only a sticker or image
stickerUrl	The image URL of the comment's sticker, or null
imageUrls	The images attached to the comment
likeCount	Likes (공감) on the comment
createdAt, updatedAt	When the comment was written and last edited (ISO 8601, UTC)
scrapedAt	When the comment was scraped (ISO 8601, UTC)

Status of each post

The key-value store record POSTS (in the Output tab: Status of each post) lists every input post with its status, the number of comments returned, and the comment count that Naver shows on the post:

[
    {
        "input": "https://blog.naver.com/blogpeople/224425969565",
        "postUrl": "https://blog.naver.com/blogpeople/224425969565",
        "status": "ok",
        "comments": 594,
        "naverCommentCount": 602
    },
    {
        "input": "https://blog.naver.com/PostView.naver?blogId=qmfosej&logNo=224430277591",
        "postUrl": "https://blog.naver.com/qmfosej/224430277591",
        "status": "comments_disabled",
        "comments": 0,
        "naverCommentCount": 31
    }
]

Status	Meaning
ok	Comments were returned
no_comments	The post has no public comments
comments_disabled	The author turned comments off. Naver then shows no comments, not even older ones
not_found	The post or blog does not exist, is private, or was deleted
invalid_url	The input is not a Naver Blog post URL
budget_reached	The run stopped at the maximum cost per run that you set, before this post ended
failed	Naver did not answer after many retries. Run the post again

How to use Naver Blog Comments Scraper

You can run the scraper in four ways: in Apify Console, with the Apify API, with the Apify API clients for JavaScript and Python, or from an AI assistant such as Claude or ChatGPT.

In Apify Console (no coding)

1. Click Try for free and sign in to Apify. A free account is enough.
2. In Post URLs, add one Naver Blog post URL per line, for example https://blog.naver.com/blogpeople/224425969565.
3. In Max comments per post, set the number of comments that you want for each post. The default is 1,000. Use 0 to get all the comments.
4. Click Start.
5. Open the Output tab. View the comments as a table, or download them as JSON, CSV, Excel, XML or HTML.

To run the scraper again with the same input, save the input as a task. Add a schedule to the task to run it every hour, day or week.

With the Apify API (HTTP)

Get your API token in Apify Console under Settings → API & Integrations. Replace <YOUR_API_TOKEN> in the examples below.

Run the scraper and get the comments in one call — good for small runs that end in less than 5 minutes:

curl -X POST "https://api.apify.com/v2/acts/hgservices~naver-blog-comments-scraper/run-sync-get-dataset-items?format=json" \
  -H "Authorization: Bearer <YOUR_API_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{ "postUrls": ["https://blog.naver.com/blogpeople/224425969565"], "maxCommentsPerPost": 200 }'

Change format=json to format=csv or format=xlsx to get a spreadsheet.

Start a large run, then read the results when it ends:

# 1. Start the run. The answer contains the run ID in data.id.
curl -X POST "https://api.apify.com/v2/acts/hgservices~naver-blog-comments-scraper/runs" \
  -H "Authorization: Bearer <YOUR_API_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{ "postUrls": ["https://blog.naver.com/blogpeople/224425969565", "https://blog.naver.com/paperchan/224438187954"], "maxCommentsPerPost": 0 }'

# 2. Check the run. Wait until data.status is SUCCEEDED.
curl "https://api.apify.com/v2/actor-runs/<RUN_ID>" \
  -H "Authorization: Bearer <YOUR_API_TOKEN>"

# 3. Download the comments.
curl "https://api.apify.com/v2/actor-runs/<RUN_ID>/dataset/items?format=json" \
  -H "Authorization: Bearer <YOUR_API_TOKEN>"

# 4. Read the status of each post.
curl "https://api.apify.com/v2/actor-runs/<RUN_ID>/key-value-store/records/POSTS" \
  -H "Authorization: Bearer <YOUR_API_TOKEN>"

With the JavaScript / Node.js client

Install the client with npm install apify-client. This example gets the comments, rebuilds the threads, and reads the status of each post:

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<YOUR_API_TOKEN>' });

const run = await client.actor('hgservices/naver-blog-comments-scraper').call({
    postUrls: ['https://blog.naver.com/blogpeople/224425969565'],
    maxCommentsPerPost: 0,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
for (const comment of items.filter((c) => !c.isReply)) {
    console.log(`${comment.authorName}: ${comment.text}`);
    for (const reply of items.filter((r) => r.parentCommentId === comment.commentId)) {
        console.log(`    ↳ ${reply.authorName}${reply.isBlogOwner ? ' (blog owner)' : ''}: ${reply.text}`);
    }
}

const status = await client.keyValueStore(run.defaultKeyValueStoreId).getRecord('POSTS');
console.log(status.value);

With the Python client

Install the client with pip install apify-client (version 3.0 or later). This example finds the most active commenters on two posts:

from collections import Counter

from apify_client import ApifyClient

client = ApifyClient("<YOUR_API_TOKEN>")

run = client.actor("hgservices/naver-blog-comments-scraper").call(run_input={
    "postUrls": [
        "https://blog.naver.com/blogpeople/224425969565",
        "https://blog.naver.com/paperchan/224438187954",
    ],
    "maxCommentsPerPost": 0,
})
if run is None:
    raise RuntimeError("The run was not found.")

comments = list(client.dataset(run.default_dataset_id).iterate_items())
commenters = Counter(c["authorBlogUrl"] for c in comments if not c["isBlogOwner"])
for blog_url, count in commenters.most_common(10):
    print(count, blog_url)

status = client.key_value_store(run.default_key_value_store_id).get_record("POSTS")
print(status["value"] if status else None)

With Claude, ChatGPT and other AI assistants (MCP)

The scraper works as a tool for AI assistants through the Apify MCP server. Your assistant finds the scraper, reads its input options, runs it, and uses the comments in its answer. You sign in to Apify the first time that you connect.

To give the assistant only this scraper, use this server URL:

https://mcp.apify.com?tools=hgservices/naver-blog-comments-scraper

To let the assistant also search and run other Actors, use https://mcp.apify.com.

Claude (claude.ai and Claude Desktop) — Go to Settings → Connectors. Add a custom connector with the server URL above.

Claude Code — Run this command:

$claude mcp add --transport http apify "https://mcp.apify.com?tools=hgservices/naver-blog-comments-scraper"

ChatGPT — Turn on Developer mode in Settings → Apps & Connectors → Advanced settings. Then go to Settings → Apps & Connectors → Create, and enter the server URL above as the MCP Server URL.

Cursor, VS Code and other MCP clients — Add the server to your MCP configuration:

{
    "mcpServers": {
        "apify": {
            "url": "https://mcp.apify.com?tools=hgservices/naver-blog-comments-scraper"
        }
    }
}

Then ask in plain language:

Use the Naver Blog Comments Scraper to get all the comments of https://blog.naver.com/blogpeople/224425969565 and summarize them in English.

Get the comments of these 5 review posts and tell me which complaints come up most often.

Is the reader sentiment positive or negative under this post? Give examples.

Integrations and scheduling

Connect the scraper to the tools that you already use with Apify integrations: Google Sheets, Slack, Zapier, Make, n8n, Airbyte, Keboola and more. Use webhooks to call your own endpoint when a run ends.

Use Schedules in Apify Console to run the scraper automatically, for example every day to collect the new comments on your campaign posts.

Good to know

• Rebuild threads. A top-level comment has parentCommentId: null. Its replies have its commentId in parentCommentId.
• Track new comments. Comments come newest first. Schedule the scraper with a small Max comments per post to get only the latest comments.
• Replies count toward the limit. Max comments per post counts top-level comments and replies together.
• Secret and deleted comments are not in the dataset. Naver does not show their text or author to visitors.

Related Actors

• Naver Blog Post Scraper — the full content of Naver Blog posts by URL.
• Naver Blog Profile Scraper — a blogger's profile, follower and visitor counts, and full post list. Use it to get the post URLs of a blog, then send them to this scraper.

FAQ

Do I need a Naver account? No. You need only an Apify account. The scraper reads the public comments that every visitor can see without an account.

Why do I get fewer comments than Naver's comment count? Naver's count includes secret comments (비밀 댓글) and deleted comments. Visitors cannot see their text or author, so the scraper skips them. Compare comments and naverCommentCount in the POSTS record.

Are replies included? Yes. Replies (답글) are in the same dataset, with isReply: true and the parentCommentId of the comment that they answer.

Why does a post with old comments show comments_disabled? When the author turns comments off, Naver hides all the comments of the post, also the old ones.

Can I scrape comments from a private post? No. The scraper reads only posts that every visitor can open. A private post gets the status not_found.

Is it legal to scrape Naver Blog comments? The scraper collects only publicly available content and never signs in. Comments contain personal data, such as names and blog IDs. Use the data in line with Naver's Terms of Service and the laws that apply to you, including personal-data rules such as Korea's PIPA and the GDPR.

Support

Did you find a bug, or do you need a field that is not here? Open an issue on the Issues tab. Custom solutions are available on request.

This scraper is not affiliated with or endorsed by Naver.