100 크레딧 무료, 카드 등록 없이
Naver Cafearticle Search API
API 한 번의 호출로 Naver Cafearticle Search 데이터를 받아 가세요. Searches cafe.naver.com. Korea's largest user-community platform (analog of Reddit subreddits / Discord servers). Returns cafe posts as PostList rows: `post.ext.title` (tags stripped, entities decoded), `post.url`, `post.content.text` (snippet), `post.author.display_name` (cafe name), and `post.author.url`. Naver publishes no date for cafe results, so rows have no `published_at` and the page says so in `_warnings` (`undated_rows`). Many cafes are member-gated; the `link` URL works only if the caller has joined the cafe (Naver returns a teaser otherwise).
2026년 10월 업데이트SocialCrawl 팀이 직접 관리해요
네이버 카페 글을 돌려줍니다. 제목과 링크, 본문 일부, 글이 올라온 카페 이름과 URL이 담깁니다. 카페 글은 네이버가 작성일을 주지 않습니다.
가입한 회원만 볼 수 있는 카페가 많아 링크를 열면 맛보기만 보이기도 하니 국내 커뮤니티 여론을 볼 때 사용하세요.
68개 플랫폼을 병렬로 검색합니다
·
TikTok·
Instagram·
YouTube·
Facebook·
X·
LinkedIn·
Reddit·
Threads·
Pinterest·
Twitch·
Truth Social·
Snapchat·
Kick·
Bluesky·
Kwai·
Rumble·
Spotify·
Apple Music·TikTok Shop·
Amazon Shop·
Google Shopping·
Trustpilot·
TripAdvisor·
Yelp·
Linktree·
Komi·
Pillar·
lnk.bio·Facebook Ads·Google Ads·LinkedIn Ads·Google Search·Google News·
Finance·
Polymarket·
Tavily·
Hacker News·
GitHub·
Perplexity·Naver·
Utility·
Universal Search
TikTok·Instagram·YouTube·Facebook·X·LinkedIn·Reddit·Threads·Pinterest·Twitch·Truth Social·Snapchat·Kick·Bluesky·Kwai·Rumble·Spotify·Apple Music·TikTok Shop·Amazon Shop·Google Shopping·Trustpilot·TripAdvisor·Yelp·Linktree·Komi·Pillar·lnk.bio·Facebook Ads·Google Ads·LinkedIn Ads·Google Search·Google News·Finance·Polymarket·Tavily·Hacker News·GitHub·Perplexity·Naver·Utility·Universal Search·TikTok·Instagram·YouTube·Facebook·X·LinkedIn·Reddit·Threads·Pinterest·Twitch·Truth Social·Snapchat·Kick·Bluesky·Kwai·Rumble·Spotify·Apple Music·TikTok Shop·Amazon Shop·Google Shopping·Trustpilot·TripAdvisor·Yelp·Linktree·Komi·Pillar·lnk.bio·Facebook Ads·Google Ads·LinkedIn Ads·Google Search·Google News·Finance·Polymarket·Tavily·Hacker News·GitHub·Perplexity·Naver·Utility·Universal Search
TikTok·Instagram·YouTube·Facebook·X·LinkedIn·Reddit·Threads·Pinterest·Twitch·Truth Social·Snapchat·Kick·Bluesky·Kwai·Rumble·Spotify·Apple Music·TikTok Shop·Amazon Shop·Google Shopping·Trustpilot·TripAdvisor·Yelp·Linktree·Komi·Pillar·lnk.bio·Facebook Ads·Google Ads·LinkedIn Ads·Google Search·Google News·Finance·Polymarket·Tavily·Hacker News·GitHub·Perplexity·Naver·Utility·Universal Search·TikTok·Instagram·YouTube·Facebook·X·LinkedIn·Reddit·Threads·Pinterest·Twitch·Truth Social·Snapchat·Kick·Bluesky·Kwai·Rumble·Spotify·Apple Music·TikTok Shop·Amazon Shop·Google Shopping·Trustpilot·TripAdvisor·Yelp·Linktree·Komi·Pillar·lnk.bio·Facebook Ads·Google Ads·LinkedIn Ads·Google Search·Google News·Finance·Polymarket·Tavily·Hacker News·GitHub·Perplexity·Naver·Utility·Universal Search
TikTok·Instagram·YouTube·Facebook·X·LinkedIn·Reddit·Threads·Pinterest·Twitch·Truth Social·Snapchat·Kick·Bluesky·Kwai·Rumble·Spotify·Apple Music·TikTok Shop·Amazon Shop·Google Shopping·Trustpilot·TripAdvisor·Yelp·Linktree·Komi·Pillar·lnk.bio·Facebook Ads·Google Ads·LinkedIn Ads·Google Search·Google News·Finance·Polymarket·Tavily·Hacker News·GitHub·Perplexity·Naver·Utility·Universal Search·TikTok·Instagram·YouTube·Facebook·X·LinkedIn·Reddit·Threads·Pinterest·Twitch·Truth Social·Snapchat·Kick·Bluesky·Kwai·Rumble·Spotify·Apple Music·TikTok Shop·Amazon Shop·Google Shopping·Trustpilot·TripAdvisor·Yelp·Linktree·Komi·Pillar·lnk.bio·Facebook Ads·Google Ads·LinkedIn Ads·Google Search·Google News·Finance·Polymarket·Tavily·Hacker News·GitHub·Perplexity·Naver·Utility·Universal Search
TikTok·Instagram·YouTube·Facebook·X·LinkedIn·Reddit·Threads·Pinterest·Twitch·Truth Social·Snapchat·Kick·Bluesky·Kwai·Rumble·Spotify·Apple Music·TikTok Shop·Amazon Shop·Google Shopping·Trustpilot·TripAdvisor·Yelp·Linktree·Komi·Pillar·lnk.bio·Facebook Ads·Google Ads·LinkedIn Ads·Google Search·Google News·Finance·Polymarket·Tavily·Hacker News·GitHub·Perplexity·Naver·Utility·Universal SearchNaver API
Cafearticle Search API로 무엇을 할 수 있을까요
Cafearticle Search 엔드포인트가 통합 스키마와 계산 필드를 담은 Naver 데이터를 한 번의 요청으로 보내드려요. 스크래핑 인프라를 직접 만들거나 유지할 필요가 없어요.
요청 예시
curl -H "x-api-key: YOUR_API_KEY" \
"https://www.socialcrawl.dev/v1/naver/cafearticle/search?query=%EC%A3%BC%EC%8B%9D&display=10&label=sponsored&relevance=filter"import requests
response = requests.get(
"https://www.socialcrawl.dev/v1/naver/cafearticle/search",
params={
'query': '주식',
'display': '10',
'label': 'sponsored',
'relevance': 'filter',
},
headers={"x-api-key": "YOUR_API_KEY"},
)
data = response.json()const response = await fetch(
"https://www.socialcrawl.dev/v1/naver/cafearticle/search?query=%EC%A3%BC%EC%8B%9D&display=10&label=sponsored&relevance=filter",
{
headers: { "x-api-key": "YOUR_API_KEY" },
},
);
const data = await response.json();함께 보내면 좋은 파라미터
label=sponsored게시물마다 유료 광고나 협찬인지 표시합니다. 추가 크레딧은 들지 않으며 의도와 분야 판정도 무료입니다.relevance=filter검색어와 관련 없는 결과를 제외합니다. 추가 크레딧은 들지 않습니다. relevance=score를 보내면 결과를 모두 남기고 관련도 점수를 붙입니다.
파라미터
| 파라미터 | 필수 | 설명 |
|---|---|---|
| query | 예 | Free-text search term (UTF-8). Required. Search short noun phrases (for example `다한증` or `다한증 수술`), which match best: Naver does not treat quotes as an exact phrase. Add `relevance=filter` to drop the rows that are not about the query. |
| display | 아니오 | Number of items to return per page. Defaults to 10, cap 100; `display=101` returns 400. |
| start | 아니오 | 1-indexed offset for pagination. Defaults to 1, cap 1000; `start=1001` returns 400. Past rank 100, `sim` and `point` pages repeat Naver's top 100: those rows are removed and counted in `_warnings` (`recycled_rows`), and an emptied page is free. Page deeper with `sort=date`. |
| sort | 아니오 | Sort order. Accepted values: sim|date. Defaults to `sim` (relevance) when the corpus supports sort. Values outside this corpus's domain are rejected with a 400 before any upstream call. `date` lists the newest first, but Naver serves only the first 1,000 rows of a query (`start` caps at 1000), so on a common word it reaches back hours or days, not months, and on a multi-word query Naver also loosens the match. Cafe rows carry no date, so `since=` cannot narrow them. (sim | date) |
| relevance | 아니오 | Optional. Without this param every row already carries computed.relevance against your query, free ({ p, sense, depth, spam }: is this row about what your query means, or a different thing that shares its words?), and nothing is dropped or reordered. score asks for it explicitly and waits for every row; filter also drops the rows that are not about your query, and lists their ids in data.relevance.dropped_ids. Your query is the topic; nothing to configure. A row that could not be judged is never dropped and carries relevance: null. Pagination is unchanged, so a filtered page can hold fewer rows. Free with your query as the topic; with relevant_to it adds 1 credit per started 25 newly judged rows (rows already judged for the same topic are free, and so is a cached page). (score | filter) |
| relevance_threshold | 아니오 | Optional, only with relevance. The probability (0 to 1) a row must reach to be kept by relevance=filter. Default 0.5. Lower keeps more rows, higher keeps fewer. |
| relevant_to | 아니오 | Optional, only with relevance. Up to 200 characters describing what you mean, used as the topic instead of the query. Use it when the query is ambiguous, for example query=cleopatra with relevant_to=Cleopatra, the IGT slot game. |
| judgments | 아니오 | Optional, on (the default) or off. By default every row gains free SocialCrawl judgments (computed.labels, and computed.relevance on search endpoints), reported in data.labels (mode default) and data.relevance (origin default), each with a status (complete, partial or skipped) and pending: the rows still being judged when the page was sent, which carry null now and are filled on your next call or cached read. Default judgments never add credits, never change an existing field, and never drop or reorder a row. off returns the page exactly as before, with none of those keys. label=none does the same. (on | off) |
| dry_run | 아니오 | Optional. When 1, return a cost preview for this labelled or relevance-filtered request without fetching the page or judging any row. data.estimate reports rows_expected, rows_cached, label_credits_min, label_credits_max and base_credits. 0 credits charged. (1) |
| fit | 아니오 | Optional. When goal, keep the rows and fields needed for the goal you pass in goal= (plus any that are uncertain, and the first and last), and replace the rest with a stub. data.held_back lists the held ids and a recall id that re-reads the full page from cache at no extra charge. Without this param the page is unchanged. (goal) |
| goal | 아니오 | Required by fit=goal. What you are trying to do, in your own words, up to 300 characters. |
| fit_tokens | 아니오 | Optional, only with fit=goal. Soft cap on how much of the page to keep, in tokens. Uncertain blocks and the first and last block are kept even if they exceed it. |
| label | 아니오 | Optional CSV of SocialCrawl labels to add to every post. Without this param every page already carries sponsored, intent and niche, free; label= adds the labels you name to them (the defaults keep running). sponsored, intent and niche are free when asked for too; mention, quality, intent with offer=, and injection add 1 credit per started 25 newly judged posts. judgments=off (or label=none) turns the default labels off. sponsored: is the post a paid or gifted promotion (p, 0 to 1), did it carry a disclosure marker such as #ad or 광고 (disclosed), is it likely paid with no marker (undisclosed), and which of the accounts it mentions does it promote (brand, or null). These are signals to review, never a finding. mention (needs brand=): is the post about that brand rather than something that shares its name (about_brand, 0 to 1), how it feels about the brand on five levels (sentiment_level 0 to 4 and sentiment_score 0 to 1, null when the post is not about the brand), is it sarcastic, which aspect it talks about (taste_or_quality, price_or_value, availability_or_delivery, health_or_safety, advertising_or_campaign, customer_service, none), and did the author buy or use it (first_hand). intent: what the author is mainly doing (label: asking_for_recommendation, comparing_options, switching_away, complaining, promoting, news_or_discussion, other, or null when unsure, with confidence), whether they read as a potential buyer rather than a seller (buyer, seller), how pressing the need is (urgency, 0 to 3), and, when you pass offer=, whether your offer would plausibly help them (fits_offer). niche: which of the 33 niches of the published taxonomy sc-niche-v1 the caption belongs to, or personal_no_niche, or other (label, confidence, taxonomy), with label null when the caption is too thin to tell or the pick is unsure. It reads the caption only, not the video. quality: how much checkable detail the caption carries (fact_density 0 to 3), whether it mainly asks for likes, replies, shares, follows or tags (engagement_bait, 0 to 1), whether it is written to provoke anger as a way to get engagement (rage_bait, 0 to 1; about the writing, never the side taken), whether it only repeats someone else's news or view (secondhand, 0 to 1), and what the post is mainly doing (post_aim: inform, opinion, sell, entertain, provoke, other). exclude=engagement_bait drops posts whose engagement_bait is 0.8 or higher. injection flags text that addresses an AI system and tries to direct it (flagged, p); it never drops or rewrites a row. A post that could not be judged carries labels: null. Posts already labelled for anyone are free, and so is a cached page. data.labels reports what was judged and billed. |
| exclude | 아니오 | Optional CSV (engagement_bait), only with label=quality. Drops posts whose engagement_bait probability is 0.8 or higher and lists their ids in data.labels.dropped_ids. A post that could not be judged is never dropped. |
| brand | 아니오 | Required by label=mention, ignored otherwise. The brand or product the posts are judged against, up to 300 characters, for example brand=Buldak. Without it label=mention is skipped with the warning label_mention_needs_brand and is not billed. |
| brand_description | 아니오 | Optional, with label=mention. One plain sentence saying what the brand is, for example brand_description=Samyang's spicy instant noodle brand. Use it when the name is also an ordinary word or another company's name. |
| offer | 아니오 | Optional, with label=intent. One or two plain sentences saying what you sell, up to 300 characters, for example offer=A web design agency that builds websites for small businesses. Adds fits_offer to every post; without it fits_offer is null. |
| label_evidence | 아니오 | Optional, only with label=. When 1, every labelled row also carries computed.labels_evidence.<preset> = { quote, sentence_index }: the sentence in the row that most clearly shows the label, copied verbatim. Absent or null when no single sentence shows it. (1) |
| since | 아니오 | Only rows published on or after this date: YYYY-MM-DD (midnight UTC) or an ISO 8601 timestamp. Rows older than it are left off each page. This list is not in date order, so the walk does not stop at the date: keep following `next_cursor`, and each page costs what a page costs even when every row on it is filtered out. A row with no date is kept. `published_after`, `start_date`, `from_date`, `publish_time` (`yesterday`, `this-week`, `this-month`, `last-3-months`, `last-6-months`) and `max_age_days` are accepted and applied as `since`. |
| until | 아니오 | Only rows published on or before this date: YYYY-MM-DD (that whole UTC day is included) or an ISO 8601 timestamp. Newer rows are left off each page and the walk does not stop, so older pages follow. A row with no date is kept. `published_before`, `end_date` and `to_date` are accepted and applied as `until`. |
응답 예시
Naver Cafearticle Search API는 무엇을 돌려주나요
모든 응답은 하나의 통합 스키마를 따라요. 크레딧을 쓰기 전에 어떤 필드가 돌아오는지, 실제 응답 본문 그대로 확인해 보세요.
응답 예시 보기
{
"success": true,
"platform": "naver",
"endpoint": "/v1/naver/cafearticle/search",
"data": {
"items": [
{
"post": {
"id": "https://cafe.naver.com/divclub/64226",
"url": "https://cafe.naver.com/divclub/64226",
"content": {
"text": "Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted).",
"media_urls": null,
"thumbnail_url": null,
"duration_seconds": null
},
"author": {
"username": null,
"display_name": "user_9f7e4c",
"avatar_url": null,
"verified": null
},
"engagement": {
"views": null,
"likes": null,
"comments": null,
"shares": null,
"saves": null
},
"flags": {
"nsfw": null,
"spoiler": null,
"pinned": null,
"deleted": false
},
"published_at": null
},
"computed": {
"engagement_rate": null,
"language": "ko",
"content_category": "other",
"estimated_reach": null
}
},
{
"post": {
"id": "https://cafe.naver.com/divclub/64087",
"url": "https://cafe.naver.com/divclub/64087",
"content": {
"text": "Sample comment text (redacted).",
"media_urls": null,
"thumbnail_url": null,
"duration_seconds": null
},
"author": {
"username": null,
"display_name": "user_9f7e4c",
"avatar_url": null,
"verified": null
},
"engagement": {
"views": null,
"likes": null,
"comments": null,
"shares": null,
"saves": null
},
"flags": {
"nsfw": null,
"spoiler": null,
"pinned": null,
"deleted": false
},
"published_at": null
},
"computed": {
"engagement_rate": null,
"language": "ko",
"content_category": "other",
"estimated_reach": null
}
}
],
"total": 35063414,
"dropped": 0
},
"credits_used": 1,
"request_id": "req_example000000",
"cached": false,
"pagination": {
"next_cursor": "sc.eyJ2IjoyLCJjIjoiMTEiLCJlIjoibmF2ZXIvY2FmZWFydGljbGUvc2VhcmNoIiwicCI6InN0YXJ0In0",
"has_more": true,
"page_size": 10
},
"credits_remaining": 9999,
"source": "captured",
"captured_at": "2026-10-02T12:40:52.841Z",
"redacted": true
}통합 응답 구조를 보여 주는 실제 샘플이에요. 필드 값은 조회한 대상에 따라 달라져요.
API 상세
Naver Cafearticle Search API는 어떻게 동작하나요
API 키와 함께 GET 요청을 보내면, 통합 스키마와 계산 필드를 담은 깔끔한 JSON이 돌아와요.
메서드
GET
응답 형식
JSON
개발자 우선
소셜 미디어 데이터를 몇 초 만에 수집하는 방법
개발자를 위한 가장 빠른 소셜 미디어 스크래핑 API. 월간 활성 사용자 100억 명 이상을 포괄하는 68개 플랫폼에서 프로필, 게시물, 댓글, 분석 데이터를 수집하세요.
모든 플랫폼을 하나의 스키마로
동일한 응답 구조로 68개 플랫폼을 조회하세요. 연동은 한 번이면 충분합니다.
단순 수집을 넘어 계산된 필드 제공
엔드포인트가 해당 지표를 지원하고 계산에 필요한 원본 값이 있을 때, 정규화된 레코드에 engagement_rate, estimated_reach, content_category, language를 함께 담아 바로 활용할 수 있습니다.
코드 한 줄 쓰기 전에, 데이터부터
Visual Data Explorer에 URL만 붙여넣으면 결과 카드와 정형화된 테이블, CSV 내보내기를 바로 사용할 수 있습니다.
import requests
response = requests.get(
'https://www.socialcrawl.dev/v1/tiktok/profile',
params={'handle': 'charlidamelio'},
headers={'x-api-key': 'sc_YOUR_API_KEY'}
)
data = response.json()[ .JSON ]
{
"success": true,
"platform": "tiktok",
"data": {
"author": {
"username": "charlidamelio",
"followers": 152400000
},
"engagement": {
"likes": 12400000000,
"engagement_rate": 0.087
},
"metadata": {
"language": "en",
"content_category": "lifestyle"
}
}
}자주 묻는 질문
자주 묻는 질문
API, 요금제, 기능에 대한 질문과 답변입니다.
문의하기네이버 카페 글은 API로 어떻게 검색하나요?
GET /v1/naver/cafearticle/search에 query로 키워드를 담아 호출하면 돼요. cafe.naver.com 커뮤니티 글에서 제목, 링크, 설명, 카페 이름, 카페 주소를 찾아 data.items로 돌려줘요. x-api-key 하나면 바로 받아봐요.
네이버 카페는 무엇이고 왜 검색하나요?
네이버 카페는 한국 최대 커뮤니티 플랫폼이에요. Reddit 서브레딧이나 Discord 서버에 가장 가까워요. 제품·취미·동네 이야기처럼 공개 웹에 잘 안 나오는 한국 사용자들의 실제 대화를 여기서 찾아볼 수 있어요.
카페 글 링크는 항상 열리나요?
항상은 아니에요. 가입한 회원만 볼 수 있는 카페가 많아서, 링크가 미리보기 수준일 때가 있어요. 그래도 제목, 설명, 카페 이름은 응답에 그대로 와서, 트렌드 파악이나 글 탐색에는 충분해요.
정렬 옵션은 어떻게 쓰나요?
sort에 sim(관련도, 기본)이나 date(최신순)를 넣을 수 있고, display·start로 페이지네이션해요. sort=date로 주기적으로 호출하면 여러 네이버 카페에서 키워드 관련 최신 대화를 따라가기 쉽고 간편해요.
네이버 카페 API 요금은 얼마인가요?
한 번 검색에 1 크레딧(스탠다드 티어)이 들고, 일치 글 수와 상관없이 동일해요. 새 계정은 신용카드 없이 100 크레딧을 무료로 받으니, 커뮤니티 검색을 100번 정도 돌려보고 시작하실 수 있어요.
AI에게 SocialCrawl을 물어보세요
Naver Cafearticle Search 데이터, 가져올 준비 되셨어요?
API 키 받고 60초 안에 Naver 데이터를 받아 가세요.