100 크레딧 무료, 카드 등록 없이
X Search Tweets API
API 한 번의 호출로 X Search Tweets 데이터를 받아 가세요. Searches X (Twitter) for tweets matching a keyword or phrase, each result with the full text, like count, retweet count, reply count, bookmark count, view count, media attachments, author info, and creation timestamp. Long-form posts return their complete body, not the 280-character clamp. t.co links in the text are resolved to their destinations. A post carrying more than one photo lists every URL in `post.ext.all_media_urls`, while `post.content.media_urls` holds the first; `post.ext.quote_count` is how many times the post was quote-tweeted. X search operators inside `query` narrow the search itself: `since:`/`until:` (YYYY-MM-DD), `from:handle`, quoted exact phrases, `filter:images`, and `filter:videos`. The `since` and `until` parameters filter the returned rows instead, and `since` ends a newest-first walk at that date. `sort` picks the ranking: `latest` (the default) returns the newest matches first, `top` returns the most POPULAR ones, which on an unquoted multi-term query means engagement-ranked rather than relevance-ranked, so `meltwater expensive contract` can return high-engagement posts about none of those things. Quote the phrase, or pin the topic with an operator such as `min_faves:20`, when you need precision from `top`. Page size is set by the source, typically around 20 tweets. To go deeper, send `pagination.next_cursor` back as `cursor` and repeat until `pagination.has_more` is false; each page costs 1 credit. When the main source cannot fetch a page, a second source answers it; a `latest` walk carries on from the last post you received, while a `top` search answered that way is one page with no cursor.
2026년 10월 업데이트SocialCrawl 팀이 직접 관리해요
키워드나 문구에 걸린 트윗을 돌려줍니다. 트윗마다 본문 전체, 좋아요와 리트윗, 답글, 북마크, 조회 수, 첨부 미디어, 작성자 정보, 작성 시각이 붙습니다.
브랜드나 주제가 X에서 어떻게 언급되는지 추적할 때 사용하세요. from:, 따옴표 문구, filter:images, since:/until: 같은 X 검색 연산자를 query에 그대로 쓸 수 있고, sort로 최신순과 인기순을 고릅니다.
69개 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 SearchX API
Search Tweets API로 무엇을 할 수 있을까요
Search Tweets 엔드포인트가 통합 스키마와 계산 필드를 담은 X 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/twitter/search/tweets?query=nike+running+shoes&label=sponsored&relevance=filter"import requests
response = requests.get(
"https://www.socialcrawl.dev/v1/twitter/search/tweets",
params={
'query': 'nike running shoes',
'label': 'sponsored',
'relevance': 'filter',
},
headers={"x-api-key": "YOUR_API_KEY"},
)
data = response.json()const response = await fetch(
"https://www.socialcrawl.dev/v1/twitter/search/tweets?query=nike+running+shoes&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 | Keyword or phrase to search tweets for. X operators inside this string narrow the search itself, for example since:YYYY-MM-DD, until:YYYY-MM-DD, from:handle, quoted phrases, min_faves:20, filter:images, and filter:videos. Quote a multi-word phrase when you want relevance rather than engagement ranking from sort=top |
| sort | 아니오 | Result ranking: latest (default) for the newest matches first, top for the most popular matches. top ranks by engagement, not relevance, so an unquoted multi-term query can return popular posts that match none of your terms. Quote the phrase or add an operator to tighten it (latest | top) |
| cursor | 아니오 | Cursor from the previous response's pagination.next_cursor to fetch the next page |
| switch_from | 아니오 | Optional brand. data.switch_receipts lists posts where the author says they personally left that brand, with the verbatim text, the reason, where they went, and a link. There is no percentage. No extra credits. |
| 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, ai_style, 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. ai_style: writing patterns common in AI-generated text, judged on the text alone. It does not say who wrote the post, and a person who writes in this style is flagged too. Six patterns are judged, each a probability (0 to 1): binary_contrast ("This is not X. It's Y."), faux_insight ("Here's what nobody tells you" and throat-clearing openers), colon_reveal ("The best part: it learns."), profound_kicker (ends on an aphorism or mic-drop line), puffery ("marks a pivotal moment", "highlighting the importance of") and rhetorical_setup ("What if I told you", a question the post answers itself, "Not a X. Not a Y. A Z."). Four are counted in the text: slop_words (words and phrases such as delve, leverage, robust, game changer, at the end of the day), em_dashes, emoji_bullets (lines that start with an emoji or a symbol bullet) and one_line_paragraphs (paragraphs that are one short line). pattern_count is how many patterns are present (a judged pattern at 0.8 or higher, slop_words 1 or more, em_dashes 2 or more, emoji_bullets 2 or more, one_line_paragraphs 5 or more) and markers lists their names, comma-separated. A post with less than about eight words of text is only counted, with every judged pattern 0. The counts read the first 400 characters of the post. exclude=ai_style drops posts with 2 or more patterns. 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, ai_style). engagement_bait, only with label=quality, drops posts whose engagement_bait probability is 0.8 or higher. ai_style, only with label=ai_style, drops posts that show 2 or more of its writing patterns (pattern_count 2 or higher). Dropped posts are listed 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 the page, and the page that reaches one ends the walk: `next_cursor` is not returned and `pagination.stopped_at` is `since`. Sending it sets the newest-first sort shown in this endpoint's sort parameter (any other sort value is a free 400). The page still costs what a page costs, so you pay for the pages you walk and no more. 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`. |
| min_views | 아니오 | Keep only rows with at least this many views (`post.engagement.views`). A row whose view count is unknown is discarded, so every returned row meets the floor. Filtering runs on our side after each page is fetched, so every page walked is billed as usual; `data.walk.discarded` counts what was removed and why. Each page is its own entry in `GET /v1/credits/transactions`, under the page's request id listed in `data.walk.request_ids`. |
| max_age_days | 아니오 | Keep only rows published within this many days (`post.published_at`), 1 to 3650. A row with no date is discarded. Filtering runs on our side after each page is fetched, so every page walked is billed as usual; `data.walk.discarded` counts what was removed and why. Each page is its own entry in `GET /v1/credits/transactions`, under the page's request id listed in `data.walk.request_ids`. |
| sort_rows | 아니오 | `views`: return the kept rows ordered by view count, highest first, across every page walked. Rows without a view count go last. (views) |
| 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; its charge and any refund are recorded under the page's own request id, listed in `data.walk.request_ids`. 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
X Search Tweets 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": "twitter",
"endpoint": "/v1/twitter/search/tweets",
"data": {
"items": [
{
"post": {
"id": "2105921048097001600",
"url": "https://x.com/user_b389f6/status/2105921048097001600",
"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_b389f6",
"display_name": "user_75597e",
"avatar_url": "https://example.com/avatars/user_16049e.png",
"verified": true
},
"engagement": {
"views": 84,
"likes": 0,
"comments": 0,
"shares": 0,
"saves": 0
},
"flags": {
"nsfw": null,
"spoiler": null,
"pinned": false,
"deleted": false
},
"published_at": "2026-10-02T07:21:18.000Z",
"ext": {
"author_followers": 586,
"author_following": 11,
"author_posts_count": 607,
"content_language": "en",
"quote_count": 0,
"all_media_urls": null
}
},
"computed": {
"engagement_rate": 0,
"language": "en",
"content_category": "business",
"estimated_reach": 101,
"relevance": null,
"labels": null
}
},
{
"post": {
"id": "2105916328628433024",
"url": "https://x.com/user_b2b619/status/2105916328628433024",
"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_b2b619",
"display_name": "user_44661d",
"avatar_url": "https://example.com/avatars/user_34343f.png",
"verified": true
},
"engagement": {
"views": 27,
"likes": 1,
"comments": 0,
"shares": 0,
"saves": 0
},
"flags": {
"nsfw": null,
"spoiler": null,
"pinned": false,
"deleted": false
},
"published_at": "2026-10-02T07:02:33.000Z",
"ext": {
"author_followers": 873,
"author_following": 1512,
"author_posts_count": 16187,
"content_language": "en",
"quote_count": 0,
"all_media_urls": null
}
},
"computed": {
"engagement_rate": 0.037037,
"language": "en",
"content_category": "other",
"estimated_reach": 32,
"relevance": null,
"labels": null
}
}
],
"total": null,
"relevance": {
"mode": "score",
"topic_source": "query",
"rows": 20,
"scored": 8,
"cached": 0,
"kept": 20,
"dropped": 0,
"dropped_ids": [],
"unjudged": 0,
"too_short": 0,
"threshold": 0.5,
"extra_credits": 0,
"methodology_version": "relevance/2",
"origin": "default",
"pending": 12,
"pending_ids": [
"2105921048097001600",
"2105916328628433024"
],
"status": "partial"
},
"labels": {
"presets": [
"sponsored",
"intent"
],
"rows": 20,
"labelled": 0,
"cached": 0,
"skipped": 0,
"unjudged": 0,
"dropped": 0,
"dropped_ids": [],
"extra_credits": 0,
"methodology_version": "labels/1",
"mode": "default",
"status": "partial",
"pending": 20,
"pending_ids": [
"2105921048097001600",
"2105916328628433024"
]
},
"dropped": 0
},
"credits_used": 1,
"request_id": "req_example000000",
"cached": false,
"pagination": {
"next_cursor": null,
"has_more": false,
"page_size": 20
},
"credits_remaining": 9999,
"source": "captured",
"captured_at": "2026-10-02T07:30:40.236Z",
"redacted": true
}통합 응답 구조를 보여 주는 실제 샘플이에요. 필드 값은 조회한 대상에 따라 달라져요.
API 상세
X Search Tweets 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 69개 플랫폼에서 프로필, 게시물, 댓글, 분석 데이터를 수집하세요.
모든 플랫폼을 하나의 스키마로
동일한 응답 구조로 69개 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"
}
}
}X Search Tweets 데이터, 가져올 준비 되셨어요?
API 키 받고 60초 안에 X 데이터를 받아 가세요.