100 크레딧 무료, 카드 등록 없이지금 시작하기
Logo
Hacker News logo
100 크레딧 무료, 카드 등록 없이

Hacker News Search API

질의어와 맞는 Hacker News 글을 제목, 링크, 작성자, 점수, 댓글 수, 게시 시각과 함께 반환합니다. tags를 주면 댓글까지 범위가 넓어집니다.

GET /v1/hackernews/search

2026년 11월 업데이트SocialCrawl 팀이 직접 관리해요

Hacker News Search API는 언제 쓰나요

키워드로 토론을 찾을 때 사용하세요. 여기서 얻은 story id를 story나 story/comments에 넘기면 상세와 댓글이 나옵니다.

API 레퍼런스 영문 원문

Searches Hacker News stories, comments, and front-page items via the Algolia HN API. Defaults to story-only results sorted by relevance. The HN Algolia index only exposes created_at_i for numeric filtering, so use numericFilters for date windows (e.g. created_at_i>1700000000). Results come back in the unified Post shape under data.items[], NOT as raw Algolia hits: each item is { post: { id, url, content, author, engagement, flags, published_at }, computed }. post.url is the Hacker News discussion permalink; the submitted article link is at post.content.media_urls; post.engagement.likes is the HN points score and post.engagement.comments is num_comments.

75개 플랫폼을 병렬로 검색합니다

·TikTok logoTikTok·Instagram logoInstagram·YouTube logoYouTube·Facebook logoFacebook·X logoX·LinkedIn logoLinkedIn·Reddit logoReddit·Threads logoThreads·Pinterest logoPinterest·Twitch logoTwitch·Truth Social logoTruth Social·Snapchat logoSnapchat·Kick logoKick·Bluesky logoBluesky·Kwai logoKwai·Rumble logoRumble·Spotify logoSpotify·Apple Music logoApple Music·TikTok Shop logoTikTok Shop·Amazon Shop logoAmazon Shop·Google Shopping logoGoogle Shopping·Trustpilot logoTrustpilot·TripAdvisor logoTripAdvisor·Yelp logoYelp·Linktree logoLinktree·Komi logoKomi·Pillar logoPillar·lnk.bio logolnk.bio·Facebook Ads logoFacebook Ads·Google Ads logoGoogle Ads·LinkedIn Ads logoLinkedIn Ads·Google Search logoGoogle Search·Google News logoGoogle News·Finance logoFinance·Polymarket logoPolymarket·Tavily logoTavily·Hacker News logoHacker News·GitHub logoGitHub·Perplexity logoPerplexity·Naver logoNaver·Utility logoUtility·Universal Search logoUniversal Search
·TikTok logoTikTok·Instagram logoInstagram·YouTube logoYouTube·Facebook logoFacebook·X logoX·LinkedIn logoLinkedIn·Reddit logoReddit·Threads logoThreads·Pinterest logoPinterest·Twitch logoTwitch·Truth Social logoTruth Social·Snapchat logoSnapchat·Kick logoKick·Bluesky logoBluesky·Kwai logoKwai·Rumble logoRumble·Spotify logoSpotify·Apple Music logoApple Music·TikTok Shop logoTikTok Shop·Amazon Shop logoAmazon Shop·Google Shopping logoGoogle Shopping·Trustpilot logoTrustpilot·TripAdvisor logoTripAdvisor·Yelp logoYelp·Linktree logoLinktree·Komi logoKomi·Pillar logoPillar·lnk.bio logolnk.bio·Facebook Ads logoFacebook Ads·Google Ads logoGoogle Ads·LinkedIn Ads logoLinkedIn Ads·Google Search logoGoogle Search·Google News logoGoogle News·Finance logoFinance·Polymarket logoPolymarket·Tavily logoTavily·Hacker News logoHacker News·GitHub logoGitHub·Perplexity logoPerplexity·Naver logoNaver·Utility logoUtility·Universal Search logoUniversal Search
·TikTok logoTikTok·Instagram logoInstagram·YouTube logoYouTube·Facebook logoFacebook·X logoX·LinkedIn logoLinkedIn·Reddit logoReddit·Threads logoThreads·Pinterest logoPinterest·Twitch logoTwitch·Truth Social logoTruth Social·Snapchat logoSnapchat·Kick logoKick·Bluesky logoBluesky·Kwai logoKwai·Rumble logoRumble·Spotify logoSpotify·Apple Music logoApple Music·TikTok Shop logoTikTok Shop·Amazon Shop logoAmazon Shop·Google Shopping logoGoogle Shopping·Trustpilot logoTrustpilot·TripAdvisor logoTripAdvisor·Yelp logoYelp·Linktree logoLinktree·Komi logoKomi·Pillar logoPillar·lnk.bio logolnk.bio·Facebook Ads logoFacebook Ads·Google Ads logoGoogle Ads·LinkedIn Ads logoLinkedIn Ads·Google Search logoGoogle Search·Google News logoGoogle News·Finance logoFinance·Polymarket logoPolymarket·Tavily logoTavily·Hacker News logoHacker News·GitHub logoGitHub·Perplexity logoPerplexity·Naver logoNaver·Utility logoUtility·Universal Search logoUniversal Search
·TikTok logoTikTok·Instagram logoInstagram·YouTube logoYouTube·Facebook logoFacebook·X logoX·LinkedIn logoLinkedIn·Reddit logoReddit·Threads logoThreads·Pinterest logoPinterest·Twitch logoTwitch·Truth Social logoTruth Social·Snapchat logoSnapchat·Kick logoKick·Bluesky logoBluesky·Kwai logoKwai·Rumble logoRumble·Spotify logoSpotify·Apple Music logoApple Music·TikTok Shop logoTikTok Shop·Amazon Shop logoAmazon Shop·Google Shopping logoGoogle Shopping·Trustpilot logoTrustpilot·TripAdvisor logoTripAdvisor·Yelp logoYelp·Linktree logoLinktree·Komi logoKomi·Pillar logoPillar·lnk.bio logolnk.bio·Facebook Ads logoFacebook Ads·Google Ads logoGoogle Ads·LinkedIn Ads logoLinkedIn Ads·Google Search logoGoogle Search·Google News logoGoogle News·Finance logoFinance·Polymarket logoPolymarket·Tavily logoTavily·Hacker News logoHacker News·GitHub logoGitHub·Perplexity logoPerplexity·Naver logoNaver·Utility logoUtility·Universal Search logoUniversal Search
Hacker News API

Search API로 무엇을 할 수 있을까요

Search 엔드포인트가 통합 스키마와 계산 필드를 담은 Hacker News 데이터를 한 번의 요청으로 보내드려요. 스크래핑 인프라를 직접 만들거나 유지할 필요가 없어요.

요청 예시

# GET /v1/hackernews/search: Metered: holds 1 credit per page up front and refunds what the call does not use. Cache hits are free and failed calls are refunded.
# Check the price first for 0 credits: add dry_run=1 to the query. Nothing is fetched or charged.
# --max-time 10: this endpoint's measured p99 latency x 1.5.
# --retry 3: retries timeouts, 429 and 5xx, honoring Retry-After.
# -o response.json keeps only the final attempt's body.
# One Idempotency-Key per request, reused on every retry, so a retried call is never charged twice.
# Next page: send pagination.next_cursor back as cursor until pagination.has_more is false.
IDEMPOTENCY_KEY=$(od -An -N16 -tx1 /dev/urandom | tr -d ' \n')
curl -sS --max-time 10 --retry 3 -o response.json \
  -H "x-api-key: YOUR_API_KEY" \
  -H "Idempotency-Key: $IDEMPOTENCY_KEY" \
  "https://www.socialcrawl.dev/v1/hackernews/search?query=claude+code&label=sponsored&relevance=filter" && cat response.json
# GET /v1/hackernews/search: Metered: holds 1 credit per page up front and refunds what the call does not use. Cache hits are free and failed calls are refunded.
# Check the price first for 0 credits: add dry_run=1 to the query. Nothing is fetched or charged.
import os
import random
import time
import uuid

import requests

API_KEY = os.environ.get("SOCIALCRAWL_API_KEY", "YOUR_API_KEY")
TIMEOUT_S = 10  # this endpoint's measured p99 latency x 1.5.
MAX_RETRIES = 3
URL = "https://www.socialcrawl.dev/v1/hackernews/search"


def backoff(attempt):
    # Exponential backoff with jitter: about 1 s, 2 s, then 4 s.
    return 2 ** attempt * (0.5 + random.random() / 2)


def socialcrawl(params):
    # One Idempotency-Key per request, reused on every retry, so a retried call is never charged twice.
    idempotency_key = str(uuid.uuid4())
    for attempt in range(MAX_RETRIES + 1):
        try:
            res = requests.get(
                URL,
                params=params,
                headers={"x-api-key": API_KEY, "Idempotency-Key": idempotency_key},
                timeout=TIMEOUT_S,
            )
            body = res.json()
        except (requests.RequestException, ValueError):
            # A timeout, a dropped connection or a non-JSON gateway page: retry with the same key.
            if attempt == MAX_RETRIES:
                raise
            time.sleep(backoff(attempt))
            continue
        if body["success"]:
            return body
        error = body["error"]
        # Branch on error["type"], never on the message text.
        if error["type"] == "RESOURCE_NOT_FOUND":
            return None  # refunded: nothing to read
        retry_after = res.headers.get("Retry-After")
        # SERVICE_UNAVAILABLE without Retry-After is a withdrawn endpoint: permanent.
        permanent = error["type"] == "SERVICE_UNAVAILABLE" and retry_after is None
        if not error.get("retryable") or permanent or attempt == MAX_RETRIES:
            raise RuntimeError(f"{error['type']}: {error['message']} (request_id {body['request_id']})")
        # Retry-After (seconds) wins; otherwise back off.
        time.sleep(float(retry_after) if retry_after else backoff(attempt))


params = {
    "query": "claude code",
    "label": "sponsored",
    "relevance": "filter",
}

# Walk the list: send pagination.next_cursor back as cursor until has_more is false.
MAX_PAGES = 10  # each page is one call
items = []
for _ in range(MAX_PAGES):
    body = socialcrawl(params)
    if body is None:
        break
    items.extend(body["data"]["items"])
    page = body.get("pagination") or {}
    if not page.get("has_more") or not page.get("next_cursor"):
        break
    params["cursor"] = page["next_cursor"]
print(f"{len(items)} items")
// GET /v1/hackernews/search: Metered: holds 1 credit per page up front and refunds what the call does not use. Cache hits are free and failed calls are refunded.
// Check the price first for 0 credits: add dry_run=1 to the query. Nothing is fetched or charged.
const API_KEY = process.env.SOCIALCRAWL_API_KEY ?? "YOUR_API_KEY";
const TIMEOUT_MS = 10_000; // this endpoint's measured p99 latency x 1.5.
const MAX_RETRIES = 3;

type Page = { next_cursor: string | null; has_more: boolean };
type SocialCrawlResponse =
  | { success: true; data: any; pagination?: Page; credits_used: number; request_id: string }
  | { success: false; error: { type: string; message: string; retryable: boolean }; request_id: string };

const sleep = (ms: number) => new Promise((resolve) => setTimeout(resolve, ms));
// Exponential backoff with jitter: about 1 s, 2 s, then 4 s.
const backoffMs = (attempt: number) => 2 ** attempt * 1000 * (0.5 + Math.random() / 2);

async function socialcrawl(url: URL) {
  // One Idempotency-Key per request, reused on every retry, so a retried call is never charged twice.
  const idempotencyKey = crypto.randomUUID();
  for (let attempt = 0; ; attempt++) {
    let res: Response;
    let body: SocialCrawlResponse;
    try {
      res = await fetch(url, {
        headers: {
          "x-api-key": API_KEY,
          "Idempotency-Key": idempotencyKey,
        },
        signal: AbortSignal.timeout(TIMEOUT_MS),
      });
      body = (await res.json()) as SocialCrawlResponse;
    } catch (error) {
      // A timeout, a dropped connection or a non-JSON gateway page: retry with the same key.
      if (attempt >= MAX_RETRIES) throw error;
      await sleep(backoffMs(attempt));
      continue;
    }
    if (body.success) return body;
    // Branch on error.type, never on the message text.
    if (body.error.type === "RESOURCE_NOT_FOUND") return null; // refunded: nothing to read
    const retryAfter = res.headers.get("Retry-After");
    // SERVICE_UNAVAILABLE without Retry-After is a withdrawn endpoint: permanent.
    const permanent = body.error.type === "SERVICE_UNAVAILABLE" && retryAfter === null;
    if (!body.error.retryable || permanent || attempt >= MAX_RETRIES) {
      throw new Error(`${body.error.type}: ${body.error.message} (request_id ${body.request_id})`);
    }
    // Retry-After (seconds) wins; otherwise back off.
    await sleep(retryAfter ? Number(retryAfter) * 1000 : backoffMs(attempt));
  }
}

const url = new URL("https://www.socialcrawl.dev/v1/hackernews/search");
url.searchParams.set("query", "claude code");
url.searchParams.set("label", "sponsored");
url.searchParams.set("relevance", "filter");

// Walk the list: send pagination.next_cursor back as cursor until has_more is false.
const MAX_PAGES = 10; // each page is one call
const items: unknown[] = [];
for (let page = 0; page < MAX_PAGES; page++) {
  const body = await socialcrawl(url);
  if (!body) break;
  items.push(...body.data.items);
  const next = body.pagination?.next_cursor;
  if (!body.pagination?.has_more || !next) break;
  url.searchParams.set("cursor", next);
}
console.log(`${items.length} items`);

함께 보내면 좋은 파라미터

  • label=sponsored 게시물마다 유료 광고나 협찬인지 표시합니다. 추가 크레딧은 들지 않으며 의도와 분야 판정도 무료입니다.
  • relevance=filter 검색어와 관련 없는 결과를 제외합니다. 추가 크레딧은 들지 않습니다. relevance=score를 보내면 결과를 모두 남기고 관련도 점수를 붙입니다.

파라미터

파라미터필수설명
query예Free-text search term.
tags아니오Algolia tag filter: comma-separated. Common values: "story", "comment", "poll", "show_hn", "ask_hn", "front_page", "author_<username>". Defaults to "story".
numericFilters아니오Algolia numeric filter expression on `created_at_i` (the only filterable numeric attribute): e.g. "created_at_i>1700000000". Combine with commas for AND. No filter is applied by default.
hitsPerPage아니오Hits per page (1-1000). Defaults to 30.
page아니오0-indexed page number for pagination.
relevance아니오Optional. 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_threshold아니오Optional, 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_to아니오Optional, 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.
judgments아니오Optional, 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_run아니오Optional. 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)
fit아니오Optional. 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)
goal아니오Required by fit=goal. What you are trying to do, in your own words, up to 300 characters.
fit_tokens아니오Optional, 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.
label아니오Optional 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 judged patterns read the first 400 and the last 150 characters of a long post, and the counts read the whole post. exclude=ai_style drops posts with 2 or more patterns. ai_written: how likely the post was written by an AI model, from SocialCrawl's own text classifier, reading the opening of the post (about 1,000 characters): p (0 to 1, calibrated), level (likely (p 0.95 or higher), possible (p 0.71 or higher) or unlikely) and model (the model name; a new name means a new scale). A post under 8 words is too short to read: p null, level too_short. It is a probability, not proof: a person can be flagged and an AI-written post can pass, and the shorter the post the less certain it is. exclude=ai_written drops likely posts. 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.
exclude아니오Optional CSV (engagement_bait, ai_style, ai_written). 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). ai_written, only with label=ai_written, drops posts whose level is likely (p 0.95 or higher), or whose p reaches your ai_written_threshold; a post too short to read is never dropped. Dropped posts are listed in data.labels.dropped_ids. A post that could not be judged is never dropped.
ai_written_threshold아니오Optional, only with label=ai_written and exclude=ai_written. The p (0 to 1) at which exclude=ai_written drops a post. Default 0.95 (level likely). 0.71 also drops possible posts: more AI posts go, and more posts by people with them.
brand아니오Required 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_description아니오Optional, 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.
offer아니오Optional, 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_evidence아니오Optional, 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)
since아니오Only 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`.
until아니오Only 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_pages아니오1 to 50 (default 1, or 50 when `max_items` or `max_credits` is sent). Walk up to this many pages in one call and return the rows from all of them. 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`, `max_items`, `max_credits`, `time_budget`, `page_error`) and `pagination.next_cursor` continues from where it stopped.
max_items아니오1 to 5000. Get more in one call: keep walking pages until the response holds at least this many rows, then stop with `data.walk.stopped: "max_items"`. The last page is returned whole (it was billed), so `data.items` can hold up to one page more than this, and `pagination.next_cursor` resumes right after it without skipping a row. Walks up to 50 pages unless `max_pages` says fewer; each page is billed as one call (a cached page is free). Add `max_credits` to cap the spend. A long walk can stop on the time budget first (`"time_budget"`): send the returned cursor with the same params to continue.
max_credits아니오1 to 100000. The most this call may spend, across every page it walks. A page starts only while the credits already spent plus that page's price (or, when higher, the most any page of this walk has cost) still fit, so the call never goes past it; the walk then stops with `data.walk.stopped: "max_credits"` and the cursor to resume. Sent alone, it walks as far as the budget goes (up to 50 pages). A value below the price of one page is a free 400 whose `error.details.page_credits` names that price. Credits a row join (`include=`) adds are known only once a page has run, so page 1 is checked against its own price.
응답 예시

Hacker News 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": "hackernews",
  "endpoint": "/v1/hackernews/search",
  "data": {
    "items": [
      {
        "post": {
          "id": "48734373",
          "url": "https://news.ycombinator.com/item?id=48734373",
          "content": {
            "text": "Sample comment text (redacted).",
            "media_urls": "https://thereallo.dev/blog/claude-code-prompt-steganography",
            "thumbnail_url": null,
            "duration_seconds": null
          },
          "author": {
            "username": "user_f52c84",
            "display_name": null,
            "avatar_url": null,
            "verified": null
          },
          "engagement": {
            "views": null,
            "likes": 2445,
            "comments": 750,
            "shares": null,
            "saves": null
          },
          "flags": {
            "nsfw": null,
            "spoiler": null,
            "pinned": null,
            "deleted": false
          },
          "published_at": "2026-06-30T15:44:24.000Z"
        },
        "computed": {
          "engagement_rate": null,
          "language": "en",
          "content_category": "other",
          "estimated_reach": null,
          "relevance": {
            "p": 0.91,
            "sense": "target",
            "depth": 1.49,
            "spam": 0.07
          },
          "labels": {
            "sponsored": {
              "p": 0.02,
              "disclosed": false,
              "undisclosed": false,
              "brand": null
            },
            "intent": {
              "label": "news_or_discussion",
              "confidence": 0.99,
              "buyer": false,
              "seller": 0.07,
              "fits_offer": null,
              "urgency": 0.06
            },
            "niche": {
              "label": "technology",
              "confidence": 1,
              "taxonomy": "sc-niche-v1"
            }
          }
        }
      },
      {
        "post": {
          "id": "43163011",
          "url": "https://news.ycombinator.com/item?id=43163011",
          "content": {
            "text": "Sample comment text (redacted).",
            "media_urls": "https://www.anthropic.com/news/claude-3-7-sonnet",
            "thumbnail_url": null,
            "duration_seconds": null
          },
          "author": {
            "username": "user_d9d625",
            "display_name": null,
            "avatar_url": null,
            "verified": null
          },
          "engagement": {
            "views": null,
            "likes": 2127,
            "comments": 963,
            "shares": null,
            "saves": null
          },
          "flags": {
            "nsfw": null,
            "spoiler": null,
            "pinned": null,
            "deleted": false
          },
          "published_at": "2025-02-24T18:28:59.000Z"
        },
        "computed": {
          "engagement_rate": null,
          "language": null,
          "content_category": "other",
          "estimated_reach": null,
          "relevance": {
            "p": 0.9,
            "sense": "target",
            "depth": 1.63,
            "spam": 0.08
          },
          "labels": {
            "sponsored": {
              "p": 0.04,
              "disclosed": false,
              "undisclosed": false,
              "brand": null
            },
            "intent": {
              "label": "news_or_discussion",
              "confidence": 0.91,
              "buyer": false,
              "seller": 0.1,
              "fits_offer": null,
              "urgency": 0.01
            },
            "niche": {
              "label": "technology",
              "confidence": 1,
              "taxonomy": "sc-niche-v1"
            }
          }
        }
      }
    ],
    "total": null,
    "relevance": {
      "mode": "score",
      "topic_source": "query",
      "rows": 2,
      "scored": 2,
      "cached": 2,
      "kept": 2,
      "dropped": 0,
      "dropped_ids": [],
      "unjudged": 0,
      "too_short": 0,
      "threshold": 0.5,
      "extra_credits": 0,
      "methodology_version": "relevance/2",
      "origin": "default",
      "pending": 0,
      "pending_ids": [],
      "status": "complete"
    },
    "labels": {
      "presets": [
        "sponsored",
        "intent"
      ],
      "rows": 2,
      "labelled": 2,
      "cached": 2,
      "skipped": 0,
      "unjudged": 0,
      "dropped": 0,
      "dropped_ids": [],
      "extra_credits": 0,
      "methodology_version": "labels/1",
      "mode": "default",
      "status": "complete",
      "pending": 0,
      "pending_ids": []
    },
    "dropped": 0
  },
  "credits_used": 1,
  "request_id": "req_example000000",
  "cached": false,
  "pagination": {
    "next_cursor": "sc.eyJ2IjoyLCJjIjoiMiIsImUiOiJoYWNrZXJuZXdzL3NlYXJjaCIsInAiOiJwYWdlIn0",
    "has_more": true,
    "page_size": 2
  },
  "credits_remaining": 9999,
  "source": "captured",
  "captured_at": "2026-10-02T13:10:39.022Z",
  "redacted": true
}

통합 응답 구조를 보여 주는 실제 샘플이에요. 필드 값은 조회한 대상에 따라 달라져요.

API 상세

Hacker News Search API는 어떻게 동작하나요

API 키와 함께 GET 요청을 보내면, 통합 스키마와 계산 필드를 담은 깔끔한 JSON이 돌아와요.

메서드

GET

응답 형식

JSON

왜 SocialCrawl인가요

Hacker News Search 데이터는 왜 SocialCrawl로 가져올까요

Hacker News 데이터 추출에서 까다로운 부분은 SocialCrawl이 가려 드려요. 통합 스키마, AI 인리치먼트, 그리고 코드에 남지 않는 플랫폼 로직까지.

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 75개 플랫폼에서 프로필, 게시물, 댓글, 분석 데이터를 수집하세요.

모든 플랫폼을 하나의 스키마로

동일한 응답 구조로 75개 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"
    }
  }
}
+ 75개 플랫폼
자주 묻는 질문

자주 묻는 질문

API, 요금제, 기능에 대한 질문과 답변입니다.

문의하기
Hacker News는 어떻게 검색하나요?
GET /v1/hackernews/search에 query 파라미터로 검색어를 담아 호출하면 돼요. 일치하는 HN 스토리와 댓글을 제목, URL, 점수, 작성자, 댓글 수, 아이템 ID와 함께 통합 data.items 스키마로 받아볼 수 있어요.
검색에 어떤 필터를 걸 수 있나요?
tags로 story, comment, show_hn, ask_hn 또는 특정 작성자로 범위를 좁히고, numericFilters로 점수·댓글 수·작성 시각 조건을 줄 수 있어요. 둘을 합치면 지난주 100점 이상 Show HN 게시물만 뽑아보는 식으로 쓸 수 있어요.
검색 결과는 어떻게 페이지네이션하나요?
hitsPerPage로 페이지 크기를 정하고 page로 페이지를 넘기면 돼요. page는 0부터 시작하고, 더 이상 결과가 오지 않을 때까지 page를 올리면 쿼리 전체 결과를 첫 페이지 너머까지 쭉 가져오실 수 있어요.
기술 트렌드나 런칭 모니터링에 쓸 수 있나요?
네, 주제·제품·도메인을 query로 넣고 주기적으로 호출하면 돼요. tags=show_hn으로 런칭만 좁혀서 수집할 수도 있어요. Reddit·GitHub 소스와 함께 기술 트렌드와 개발자 반응 모니터링 파이프라인을 쉽고 간편하게 구축하실 수 있어요.
Hacker News Search API는 요금이 얼마인가요?
한 번 호출에 1 크레딧(스탠다드 티어)이 들고, 결과 개수와 상관없이 동일해요. 새 계정은 신용카드 없이 100 크레딧을 무료로 받아서 파이프라인을 만드는 동안 검색을 100번 정도 돌려보실 수 있어요.

AI에게 SocialCrawl을 물어보세요

Hacker News Search 데이터, 가져올 준비 되셨어요?

API 키 받고 60초 안에 Hacker News 데이터를 받아 가세요.

무료로 시작하기

🤖 AI 에이전트나 LLM이신가요? 이 페이지를 markdown으로 읽어보세요