100 크레딧 무료, 카드 등록 없이
Threads Search API
API 한 번의 호출로 Threads Search 데이터를 받아 가세요. Searches Threads for posts matching a keyword query. Returns a list of matching posts with text content, like counts, author info, and creation timestamps. Posts filed under a Threads topic tag also carry that tag name at `post.ext.topic_tag` (e.g. `bali`, `dokter gigi`) with its stable id at `post.ext.topic_tag_id`, so you can group or filter results by topic client-side; both are absent on untagged posts, which are the majority. Threads exposes no tags-only search mode upstream, so this stays a keyword query. Search rows carry the same media shape as the other post lanes: carousel posts return every slide as an array in `content.media_urls`, video posts return a playable video URL there with the cover frame in `content.thumbnail_url`, and a quote post's attached content is recoverable at `post.ext.quoted_post`. `post.ext.quote_count` and `post.ext.reshare_count` complete the reshare picture that `engagement.shares` only starts. `engagement.views` and `post.flags.pinned` are null on a plain call, because Threads publishes them only on `/v1/threads/post`; send `include=engagement` and the first 20 posts are looked up there by permalink in the same call, and only those two leaves (plus a missing display name) are copied onto each row. You are billed 1 credit for each post whose view count or display name was filled. Threads publishes a view count only once it has one, so a post that is minutes old usually comes back without one: that row still gets its pinned flag, and it is free. The join adds 3 to 12 seconds (never more than 12), and a `data.hydration` block reports the rows looked up, filled and served from cache and the credits held and kept; a post the lookup could not read at all is refunded and named by `data._warnings: ["engagement_partial"]`. It is refused beside a `limit` above 20: page with the cursor instead, 20 posts a call. Each response is one result window (typically 15-20 posts); page deeper by sending back pagination.next_cursor as cursor, or set limit (1-100) to have the API walk multiple windows server-side until it has collected at least that many unique posts, billed per window consumed (1 credit each, unused window budget refunded). limit is a collection target rather than a page size, so a response usually carries somewhat more than you asked for; nothing you were billed for is trimmed away. Those windows run sequentially at roughly 3.4 seconds each, so limit buys posts with wall clock as well as credits: measured 07/09/2026 cache-cold, a single window is 3.5s while limit=50 is 10.2s and limit=100 is 19.5s. Set your client timeout above the limit you ask for, or page with the cursor instead. start_date and end_date bound the search to a period; the cursor walk stays inside those bounds. Multi-word queries are handled for you: Threads matches a search against the topic tags it already knows rather than scoring individual terms, so a longer phrase it does not recognise returns nothing at all rather than fewer results. When that happens the query is automatically relaxed into its adjacent word pairs (for example `cari vendor mesin kopi jakarta` becomes `cari vendor`, `vendor mesin`, `mesin kopi` and `kopi jakarta`), those searches run in parallel, and the results come back merged, de-duplicated and ordered by how many of your terms each post contains. You are billed 1 credit for each relaxed search that returned posts and nothing for the ones that did not, so a query that already worked costs exactly what it always did. An expanded response is a single page and carries no pagination cursor, and `data._warnings` names every sub-query that ran. Relaxation respects start_date and end_date: posts outside your window are dropped from every sub-query, and a sub-query left with nothing inside the window is not billed. It also never fires on a request that carried a cursor, so the last hop of a pagination loop is the honest end of the walk rather than a surprise page of loosely related posts. Send expand=false to search the exact phrase only.
2026년 10월 업데이트SocialCrawl 팀이 직접 관리해요
키워드에 맞는 Threads 글을 반환합니다. 글마다 본문과 좋아요 수, 작성자, 작성 시각, 글이 속한 토픽 태그(post.ext.topic_tag)가 나오고, 더 예전 글로 넘어갈 커서도 함께 옵니다.
Threads 전체에서 주제로 글을 찾을 때 사용하세요. pagination.next_cursor를 따라가면 계속 이어 볼 수 있고, limit(최대 100)을 주면 한 번의 호출로 여러 페이지를 모아 받습니다. start_date와 end_date로 기간도 좁힐 수 있습니다.
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 SearchThreads API
Search API로 무엇을 할 수 있을까요
Search 엔드포인트가 통합 스키마와 계산 필드를 담은 Threads 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/threads/search?query=artificial+intelligence&label=sponsored&relevance=filter&trim=true"import requests
response = requests.get(
"https://www.socialcrawl.dev/v1/threads/search",
params={
'query': 'artificial intelligence',
'label': 'sponsored',
'relevance': 'filter',
'trim': 'true',
},
headers={"x-api-key": "YOUR_API_KEY"},
)
data = response.json()const response = await fetch(
"https://www.socialcrawl.dev/v1/threads/search?query=artificial+intelligence&label=sponsored&relevance=filter&trim=true",
{
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.trim=true가격은 같습니다. 용량이 큰 원본 필드를 빼서 응답이 가벼워집니다.
파라미터
| 파라미터 | 필수 | 설명 |
|---|---|---|
| query | 예 | Search keyword or phrase to find Threads posts |
| start_date | 아니오 | Inclusive start of the search period (YYYY-MM-DD). Pagination never walks past it, and a relaxed query drops any post older than it. Threads treats the date pair as a ranking hint rather than a filter, so the window is enforced on our side: a post we cannot date is treated as outside it. |
| end_date | 아니오 | Inclusive end of the search period (YYYY-MM-DD). Pagination starts here and walks back in time, and a relaxed query drops any post newer than it. |
| trim | 아니오 | Ask the upstream for a stripped record. This is a real shape change, not just less whitespace: a trimmed row carries only the id, text, shortcode, like count, timestamp and author, so media, reply count, share count, view count, topic tag, pinned flag and quoted post all come back null. Same 1 credit either way, so send it only when the text and the like count are all you need. |
| cursor | 아니오 | Opaque cursor from a prior response's pagination.next_cursor, passed back verbatim, to fetch the next (older) result window. It carries your date bounds, so paging cannot escape the period you asked for. A request that sends a cursor is never query-relaxed. |
| limit | 아니오 | Collect AT LEAST this many unique posts in one call (1-100). This is a collection target, not a page size: the API walks whole result windows server-side until it has collected this many (or the query runs dry), so the response usually carries somewhat more than you asked for and never fewer unless the query ran out. Nothing you paid for is trimmed away. Billed 1 credit per window consumed (about 15-20 posts each), with the unused window budget refunded. Omit for a single window. BUDGET FOR THE WALL CLOCK: the windows run one after another, at roughly 3.4 seconds each, so a high limit is a long request. Measured on production 07/09/2026, cache-cold: no limit 3.5s for 20 posts, limit=30 7.3s for 37, limit=50 10.2s for 55, limit=100 19.5s for 111. If your HTTP client defaults to a 10-second timeout, limit=50 and above will not fit inside it. Either raise the client timeout, or ask for a smaller limit and page with pagination.next_cursor, which costs the same credits for the same posts. |
| expand | 아니오 | Set to false to search the exact phrase only. Defaults to true, which relaxes a query Threads does not recognise into its adjacent word pairs and merges the results, billing 1 credit per relaxed search that returned posts inside your date window. Ignored on a request that carries a cursor. |
| include | 아니오 | Send `engagement` to fill `engagement.views` and `post.flags.pinned` on the first 20 posts by looking each one up on `/v1/threads/post` in the same call. 1 credit per post whose view count or display name was filled from a fresh lookup (20 at most); posts served from that lookup's cache (10 minutes) are free, and so is a post Threads has published no view count for yet, which still gets its pinned flag. Adds 3 to 12 seconds, never more than 12. One token only: `engagement`. Not accepted with a `limit` above 20; page with the cursor for more. (engagement) |
| 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`. |
| max_pages | 아니오 | 1 to 5 (default 1). Walk up to this many pages in one call and return the rows from all of them (after any filter). Each page walked is billed exactly as one call to this endpoint (a cached page is free) and counts against your rate limit. The walk stops early at the last page, or when the request's time budget runs low; `data.walk.stopped` says why (`end`, `max_pages`, `time_budget`, `page_error`) and `data.next_cursor` continues from where it stopped. |
| seen | 아니오 | An id you choose (1 to 64 letters, digits, `.`, `_` or `-`). Rows your account already received under the same `seen` id are removed from the page, and the page price falls with the share of repeats: page credits x new rows / rows on the page, rounded up, so a page of nothing but repeats is free. Only the page's own price is discounted: credits for joined data (`include=`) are charged only for rows you have not received, and are never discounted. The memory lasts 24 hours from the last call that used the id, holds row ids only, and is private to your account. Use one id across a set of related searches; `data.walk.repeats` counts what was removed. |
응답 예시
Threads 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": "threads",
"endpoint": "/v1/threads/search",
"data": {
"items": [
{
"post": {
"id": "3998890680578542448",
"url": "https://www.threads.com/@user_4317b4/post/Dd-6eMPgQtw",
"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": "user_4317b4",
"display_name": "user_74c21a",
"avatar_url": "https://example.com/avatars/user_bab3c1.png",
"verified": false
},
"engagement": {
"views": null,
"likes": 5,
"comments": 1,
"shares": 0,
"saves": null
},
"flags": {
"nsfw": null,
"spoiler": null,
"pinned": null,
"deleted": false
},
"published_at": "2026-10-02T07:08:58.000Z",
"ext": {
"published_at_epoch": 1790924938,
"quote_count": 0,
"topic_tag": null,
"reshare_count": null,
"topic_tag_id": null
}
},
"computed": {
"engagement_rate": null,
"language": "en",
"content_category": "other",
"estimated_reach": null,
"relevance": {
"p": 0.46,
"sense": "target",
"depth": 1.03,
"spam": 0.05
},
"labels": null
}
},
{
"post": {
"id": "3998600807021823393",
"url": "https://www.threads.com/@user_5cca78/post/Dd94j-dIEWh",
"content": {
"text": "Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted). 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": "user_5cca78",
"display_name": "user_c565e9",
"avatar_url": "https://example.com/avatars/user_de4ca5.png",
"verified": false
},
"engagement": {
"views": null,
"likes": 1,
"comments": 1,
"shares": 1,
"saves": null
},
"flags": {
"nsfw": null,
"spoiler": null,
"pinned": null,
"deleted": false
},
"published_at": "2026-10-01T21:33:03.000Z",
"ext": {
"published_at_epoch": 1790890383,
"quote_count": 0,
"topic_tag": "tinfoilhat",
"reshare_count": null,
"topic_tag_id": "18415724197038380"
}
},
"computed": {
"engagement_rate": null,
"language": "en",
"content_category": "other",
"estimated_reach": null,
"relevance": {
"p": 0.83,
"sense": "target",
"depth": 1.48,
"spam": 0.18
},
"labels": null
}
}
],
"next_cursor": "dw1.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",
"total": null,
"relevance": {
"mode": "score",
"topic_source": "query",
"rows": 20,
"scored": 19,
"cached": 1,
"kept": 20,
"dropped": 0,
"dropped_ids": [],
"unjudged": 0,
"too_short": 1,
"threshold": 0.5,
"extra_credits": 0,
"methodology_version": "relevance/2",
"origin": "default",
"pending": 0,
"pending_ids": [],
"status": "complete"
},
"labels": {
"presets": [
"sponsored",
"intent"
],
"rows": 20,
"labelled": 7,
"cached": 0,
"skipped": 1,
"unjudged": 0,
"dropped": 0,
"dropped_ids": [],
"extra_credits": 0,
"methodology_version": "labels/1",
"mode": "default",
"status": "partial",
"pending": 12,
"pending_ids": [
"3998890680578542448",
"3998600807021823393"
]
},
"dropped": 0
},
"credits_used": 1,
"request_id": "req_example000000",
"cached": false,
"pagination": {
"next_cursor": "sc.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",
"has_more": true,
"page_size": 20
},
"credits_remaining": 9999,
"source": "captured",
"captured_at": "2026-10-02T07:26:34.862Z",
"redacted": true
}통합 응답 구조를 보여 주는 실제 샘플이에요. 필드 값은 조회한 대상에 따라 달라져요.
API 상세
Threads 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.
문의하기Threads에서 키워드로 게시물을 어떻게 검색하나요?
GET /v1/threads/search에 query 파라미터로 키워드를 담아 호출하면 돼요. 매칭된 게시물 배열이 본문, 좋아요 수, 작성자 정보, 작성 시각과 함께 JSON으로 와요.
검색 결과를 기간으로 필터링할 수 있나요?
네, 선택 파라미터인 start_date와 end_date를 함께 보내면 해당 기간의 게시물만 받아볼 수 있어요. 캠페인 기간 언급 추적이나 시점별 리포트 작성에 쉽고 간편하게 활용할 수 있어요.
각 검색 결과에는 어떤 데이터가 포함되나요?
결과마다 게시물 id, 본문, 좋아요 수, 답글 수, 재게시 수, 조회 수, 작성자 핸들과 이름, 인증 여부, 게시 시각이 통합 스키마로 함께 와요.
사용자 검색과는 어떻게 다른가요?
search는 키워드와 매칭되는 게시물을 찾아줘요. 사용자 계정을 찾고 싶다면 search/users를 쓰세요. 소셜 리스닝에는 search, 크리에이터 발굴에는 search/users가 딱이에요.
Threads Search API는 요금이 얼마인가요?
한 번 검색에 1 크레딧(스탠다드 티어)이 소진돼요. 새 계정에는 100 크레딧이 무료로 제공돼서 신용카드 없이 100번의 키워드 검색을 미리 테스트해 보실 수 있어요.
AI에게 SocialCrawl을 물어보세요
Threads Search 데이터, 가져올 준비 되셨어요?
API 키 받고 60초 안에 Threads 데이터를 받아 가세요.