Prism Adverse Screen API
API 한 번의 호출로 Prism Adverse Screen 데이터를 받아 가세요. Reads the recent public posts of a person's own profiles (one per platform: `linkedin`, `twitter`, `facebook`, `instagram`, `threads`, `tiktok`, each a handle or a profile URL) and asks, post by post, whether the author engages in, admits, threatens or promotes each category you screen for: `fraud_or_financial_crime`, `violence_or_threats`, `hate_or_harassment`, `drugs`, `sanctions_or_terror_links`, `sexual_misconduct`, `reputational_other` (default: all). A separate check keeps posts that report, quote, warn about or condemn what someone else did (news, a scam warning) from counting as the author's conduct, and a severity level (1 minor, 2 serious, 3 severe) is given for every flagged post. Every entry of `flags` cites its post (`platform`, `post_id`, `url`, `published_at`, an `excerpt`) with the probability for each requested category; `category_counts` counts flagged and uncertain posts per category; `requires_review` is true when any post is flagged. With `name` (and optionally `employer`, `city`), each profile is first checked against the named person: only profiles judged to be the person's own are screened, the rest are listed in `profiles` with the identity verdict and are not screened (`screen_unconfirmed=true` screens possible matches too, never a profile judged to be someone else). These are automated labels for a human reviewer, not a decision: there is no summary, verdict or score about the person, and political opinion, religion, health, sexuality and other personal characteristics are never screened. Public posts only; private accounts return nothing. `screen_complete` is false when a profile or a post could not be screened, and `_warnings` says why.
2026년 9월 업데이트SocialCrawl 팀이 직접 관리해요
본인 공개 프로필의 게시물 가운데 검토가 필요한 글을 반환합니다. 표시된 글마다 원문 게시물과 유형별 확률, 심각도가 붙고 유형별 건수도 함께 나옵니다.
채용 전 평판 조회나 KYC에서 후보자의 게시물을 일일이 읽지 않고 문제 게시물을 찾을 때 사용하세요. 최종 판단은 검토 담당자가 합니다.
65개 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 SearchTikTok·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 SearchTikTok·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 SearchTikTok·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 SearchAdverse Screen API로 무엇을 할 수 있을까요
Adverse Screen 엔드포인트가 통합 스키마와 계산 필드를 담은 Prism 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/prism/adverse-screen?twitter=elonmusk&name=Elon+Musk&categories=fraud_or_financial_crime%2Cviolence_or_threats"import requests
response = requests.get(
"https://www.socialcrawl.dev/v1/prism/adverse-screen",
params={
'twitter': 'elonmusk',
'name': 'Elon Musk',
'categories': 'fraud_or_financial_crime,violence_or_threats',
},
headers={"x-api-key": "YOUR_API_KEY"},
)
data = response.json()const response = await fetch(
"https://www.socialcrawl.dev/v1/prism/adverse-screen?twitter=elonmusk&name=Elon+Musk&categories=fraud_or_financial_crime%2Cviolence_or_threats",
{
headers: { "x-api-key": "YOUR_API_KEY" },
},
);
const data = await response.json();파라미터
| 파라미터 | 필수 | 설명 |
|---|---|---|
| 아니오 | LinkedIn profile URL (linkedin.com/in/...) or the profile slug. | |
| 아니오 | X (Twitter) handle or profile URL. | |
| 아니오 | Facebook profile or page URL, or its username. | |
| 아니오 | Instagram handle or profile URL. | |
| threads | 아니오 | Threads handle or profile URL. |
| tiktok | 아니오 | TikTok handle or profile URL. |
| name | 아니오 | The person's full name. When set, each profile is checked against it before screening. |
| employer | 아니오 | Optional current employer, used only for the identity check. |
| city | 아니오 | Optional city or country, used only for the identity check. |
| categories | 아니오 | Comma-separated subset of fraud_or_financial_crime, violence_or_threats, hate_or_harassment, drugs, sanctions_or_terror_links, sexual_misconduct, reputational_other. Default: all. An unknown member is a 400. |
| since | 아니오 | Only screen posts published on or after this date (YYYY-MM-DD). |
| limit | 아니오 | Most recent posts screened per profile, 1 to 100 (default 50). One timeline page is read per profile. |
| screen_unconfirmed | 아니오 | Set true to also screen profiles whose identity is possible or could not be judged. Profiles judged to be someone else are never screened. |
Prism Adverse Screen 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": "instagram",
"endpoint": "/v1/instagram/engagement",
"data": {
"engagement_rate_percentages": 38.33,
"recent_posts": 12,
"followers": 87608035,
"comments": 528912,
"likes": 33049046,
"recent_posts_explanation": "Statistics based on the last 12 posts",
"id_user": "2278169415",
"username": "mrbeast",
"is_private": false,
"posts_details": [
{
"likes": 5636982,
"comments": 69484,
"taken_at": 1781457954,
"datetime": "2026-06-14 20:25:54",
"hours_since_post": 461,
"time_ago": "19 days ago",
"likes_per_hour": 12228,
"comments_per_hour": 151
},
{
"likes": 20000768,
"comments": 223510,
"taken_at": 1732824650,
"datetime": "2024-11-28 23:10:50",
"hours_since_post": 13971,
"time_ago": "2 years ago",
"likes_per_hour": 1432,
"comments_per_hour": 16
},
{
"likes": 929226,
"comments": 30633,
"taken_at": 1782232475,
"datetime": "2026-06-23 19:34:35",
"hours_since_post": 246,
"time_ago": "10 days ago",
"likes_per_hour": 3777,
"comments_per_hour": 125
},
{
"likes": 487761,
"comments": 22482,
"taken_at": 1781799425,
"datetime": "2026-06-18 19:17:05",
"hours_since_post": 366,
"time_ago": "15 days ago",
"likes_per_hour": 1333,
"comments_per_hour": 61
},
{
"likes": 712265,
"comments": 15716,
"taken_at": 1781366405,
"datetime": "2026-06-13 19:00:05",
"hours_since_post": 487,
"time_ago": "20 days ago",
"likes_per_hour": 1463,
"comments_per_hour": 32
},
{
"likes": 1475116,
"comments": 35386,
"taken_at": 1781277094,
"datetime": "2026-06-12 18:11:34",
"hours_since_post": 512,
"time_ago": "21 days ago",
"likes_per_hour": 2881,
"comments_per_hour": 69
},
{
"likes": 1108220,
"comments": 26632,
"taken_at": 1780160249,
"datetime": "2026-05-30 19:57:29",
"hours_since_post": 822,
"time_ago": "1 months ago",
"likes_per_hour": 1348,
"comments_per_hour": 32
},
{
"likes": 542948,
"comments": 28476,
"taken_at": 1779375582,
"datetime": "2026-05-21 17:59:42",
"hours_since_post": 1040,
"time_ago": "1 months ago",
"likes_per_hour": 522,
"comments_per_hour": 27
},
{
"likes": 698514,
"comments": 24401,
"taken_at": 1779120014,
"datetime": "2026-05-18 19:00:14",
"hours_since_post": 1111,
"time_ago": "2 months ago",
"likes_per_hour": 629,
"comments_per_hour": 22
},
{
"likes": 468000,
"comments": 13548,
"taken_at": 1778947209,
"datetime": "2026-05-16 19:00:09",
"hours_since_post": 1159,
"time_ago": "2 months ago",
"likes_per_hour": 404,
"comments_per_hour": 12
},
{
"likes": 526594,
"comments": 24411,
"taken_at": 1777737719,
"datetime": "2026-05-02 19:01:59",
"hours_since_post": 1495,
"time_ago": "2 months ago",
"likes_per_hour": 352,
"comments_per_hour": 16
},
{
"likes": 462652,
"comments": 14233,
"taken_at": 1777580305,
"datetime": "2026-04-30 23:18:25",
"hours_since_post": 1538,
"time_ago": "2 months ago",
"likes_per_hour": 301,
"comments_per_hour": 9
}
]
},
"credits_used": 5,
"credits_remaining": 9999,
"request_id": "req-8Kq2ZmR4vT9xLb3P",
"cached": false
}Instagram API에서 가져온 예시예요. 모든 SocialCrawl 엔드포인트가 똑같은 통합 스키마를 돌려주기 때문에, Prism Adverse Screen 응답도 같은 필드로 구성돼요.
Prism Adverse Screen API는 어떻게 동작하나요
API 키와 함께 GET 요청을 보내면, 통합 스키마와 계산 필드를 담은 깔끔한 JSON이 돌아와요.
메서드
GET
응답 형식
JSON
소셜 미디어 데이터를 몇 초 만에 수집하는 방법
개발자를 위한 가장 빠른 소셜 미디어 스크래핑 API. 월간 활성 사용자 100억 명 이상을 포괄하는 65개 플랫폼에서 프로필, 게시물, 댓글, 분석 데이터를 수집하세요.
모든 플랫폼을 하나의 스키마로
동일한 응답 구조로 65개 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(){
"success": true,
"platform": "tiktok",
"data": {
"author": {
"username": "charlidamelio",
"followers": 152400000
},
"engagement": {
"likes": 12400000000,
"engagement_rate": 0.087
},
"metadata": {
"language": "en",
"content_category": "lifestyle"
}
}
}Prism Adverse Screen 데이터, 가져올 준비 되셨어요?
API 키 받고 60초 안에 Prism 데이터를 받아 가세요.