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100 크레딧 무료, 카드 등록 없이

Reddit Post Comments API

API 한 번의 호출로 Reddit Post Comments 데이터를 받아 가세요. Returns the full threaded comment tree for a Reddit post. Nested replies are auto-expanded by following upstream pagination, so a single call returns the deep tree (not just top-level comments). Each comment includes the author, body, score, direct-reply count, creation timestamp, its nesting depth at `ext.depth`, and a recursive `replies[]` array. `items[]` holds only the top-level comments, so `items.length` and `pagination.page_size` count those alone; `data.comments_returned` counts every comment in the response, replies included, and is the number to compare with the post's comment count. Comment bodies are Reddit's own markdown source, so `comment.text` can contain markdown such as `**bold**` and `[label](url)`. Comment ids are unique within a response: cursor windows can re-offer a boundary node, and those are de-duplicated before the tree is returned. Very large threads are bounded, and `data.truncated` tells you whether more of the thread exists than the response carries. It is not simply a record of our own paging: a response that reached the source's end of the thread is still reported as `truncated: true` when it falls far short of the post's own comment count, because that end is the end of one ranking window rather than the end of the thread. So `truncated: true` can arrive with no `next_cursor`, which means the thread is incomplete and this endpoint cannot fetch you the rest. A whole thread pages from one top-level cursor, so `ext.replies_cursor` on an individual branch is rare. `truncated: false` means the response looks complete against the post's own count, which is normally still higher than the comments you receive because Reddit counts removed, deleted, and filtered replies that no listing returns to anyone. `items[]` can also contain a comment whose own parent was removed upstream: it sits at the top level beside the real roots, and `parent_id` is what separates them, because a root's `parent_id` equals its `post_id` and an orphan's does not.

2026년 10월 업데이트SocialCrawl 팀이 직접 관리해요

무료로 시작하기문서 보기

게시물의 댓글 트리를 통째로 돌려줍니다. 댓글마다 작성자, 본문, 점수, 직접 답글 수, 중첩 깊이, 작성 시각, 하위 답글이 들어갑니다.

최상위 댓글만이 아니라 토론 전체가 필요할 때 사용하세요. data.truncated를 보세요. true면 스레드가 다 담기지 않았다는 뜻이니 커서가 오는 동안 계속 넘기면 됩니다.

68개 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
Reddit API

Post Comments API로 무엇을 할 수 있을까요

Post Comments 엔드포인트가 통합 스키마와 계산 필드를 담은 Reddit 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/reddit/post/comments?url=https%3A%2F%2Fwww.reddit.com%2Fr%2FNoteTaking%2Fcomments%2F1o9s55r%2Fi_tried_all_popular_ai_notetaking_apps_so_you%2F&label=purchase_intent&trim=true"
import requests

response = requests.get(
    "https://www.socialcrawl.dev/v1/reddit/post/comments",
    params={
    'url': 'https://www.reddit.com/r/NoteTaking/comments/1o9s55r/i_tried_all_popular_ai_notetaking_apps_so_you/',
    'label': 'purchase_intent',
    'trim': 'true',
    },
    headers={"x-api-key": "YOUR_API_KEY"},
)

data = response.json()
const response = await fetch(
  "https://www.socialcrawl.dev/v1/reddit/post/comments?url=https%3A%2F%2Fwww.reddit.com%2Fr%2FNoteTaking%2Fcomments%2F1o9s55r%2Fi_tried_all_popular_ai_notetaking_apps_so_you%2F&label=purchase_intent&trim=true",
  {
    headers: { "x-api-key": "YOUR_API_KEY" },
  },
);

const data = await response.json();

함께 보내면 좋은 파라미터

  • label=purchase_intent 댓글마다 구매 의사가 있는지 표시합니다. 추가 크레딧은 들지 않으며 감정, 질문, 불만 판정도 무료입니다.
  • trim=true 가격은 같습니다. 용량이 큰 원본 필드를 빼서 응답이 가벼워집니다.

파라미터

파라미터필수설명
url예Full URL of the Reddit post to fetch comments for
cursor아니오Cursor to get more comments, or replies.
trim아니오Accepted, but not honoured on this endpoint: the source that serves it does not offer a trimmed shape, so the response is the same either way. Kept because removing an accepted parameter would break existing calls.
label아니오Optional CSV of SocialCrawl labels to add to every comment: sentiment, spam, question, purchase_intent, complaint, toxic, low_quality, injection. Without this param every page already carries sentiment, question, purchase_intent and complaint, free; label= adds the labels you name to them (the defaults keep running). Each comment gains computed.labels with probabilities (0 to 1), so you choose the cut-off; a comment that could not be judged carries labels: null. sentiment, question, purchase_intent and complaint are free when asked for too; spam, toxic, low_quality and injection add 1 credit per started 25 newly judged comments (comments already labelled for anyone are free, and so is a cached page). injection flags text that addresses an AI system and tries to direct it (flagged, p); it never drops or rewrites a row. judgments=off (or label=none) turns the default labels off. data.labels reports what was judged and billed.
exclude아니오Optional CSV (spam, low_quality), only with the same preset in label. Drops comments whose probability is 0.8 or higher and lists their ids in data.labels.dropped_ids. A comment that could not be judged is never dropped.
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)
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)
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.
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`.
응답 예시

Reddit Post Comments 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": "reddit",
  "endpoint": "/v1/reddit/post/comments",
  "data": {
    "items": [
      {
        "comment": {
          "id": "nk4bu00",
          "url": "https://example.com/redacted",
          "parent_id": "1o9s55r",
          "post_id": "1o9s55r",
          "text": "Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted).",
          "author": {
            "username": "user_0dc293",
            "display_name": "user_d96928",
            "avatar_url": "https://example.com/avatars/user_918b31.png",
            "verified": null
          },
          "engagement": {
            "likes": 7,
            "replies": 1
          },
          "flags": {
            "pinned": null,
            "deleted": false
          },
          "published_at": "2025-10-18T10:27:59.144Z",
          "ext": {
            "depth": 0,
            "published_at_epoch": 1760783279
          },
          "replies": [
            {
              "id": "nnbr72r",
              "url": "https://example.com/redacted",
              "parent_id": "nk4bu00",
              "post_id": "1o9s55r",
              "text": "Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted).",
              "author": {
                "username": "user_bec0fc",
                "display_name": "user_47ef50",
                "avatar_url": "https://example.com/avatars/user_63d5a5.png",
                "verified": null
              },
              "engagement": {
                "likes": 1,
                "replies": null
              },
              "flags": {
                "pinned": null,
                "deleted": false
              },
              "published_at": "2025-11-05T23:14:00.172Z",
              "ext": {
                "depth": 1,
                "published_at_epoch": 1762384440
              }
            }
          ]
        },
        "computed": {
          "language": "en",
          "labels": {
            "sentiment": {
              "level": 3,
              "score_0_1": 0.78,
              "confidence": 0.91
            },
            "question": {
              "p": 0.03
            },
            "purchase_intent": {
              "p": 0.15
            },
            "complaint": {
              "p": 0.03
            }
          }
        }
      },
      {
        "comment": {
          "id": "nk4ee40",
          "url": "https://example.com/redacted",
          "parent_id": "1o9s55r",
          "post_id": "1o9s55r",
          "text": "Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted).",
          "author": {
            "username": "user_d43641",
            "display_name": "user_5d003e",
            "avatar_url": "https://example.com/avatars/user_bf53d9.png",
            "verified": null
          },
          "engagement": {
            "likes": 7,
            "replies": null
          },
          "flags": {
            "pinned": null,
            "deleted": false
          },
          "published_at": "2025-10-18T10:52:23.370Z",
          "ext": {
            "depth": 0,
            "published_at_epoch": 1760784743
          }
        },
        "computed": {
          "language": "en",
          "labels": {
            "sentiment": {
              "level": 1,
              "score_0_1": 0.24,
              "confidence": 0.96
            },
            "question": {
              "p": 0.03
            },
            "purchase_intent": {
              "p": 0.03
            },
            "complaint": {
              "p": 0.96
            }
          }
        }
      }
    ],
    "total": null,
    "truncated": false,
    "labels": {
      "presets": [
        "sentiment",
        "question"
      ],
      "rows": 33,
      "labelled": 33,
      "cached": 33,
      "skipped": 0,
      "unjudged": 0,
      "dropped": 0,
      "dropped_ids": [],
      "extra_credits": 0,
      "methodology_version": "labels/1",
      "mode": "default",
      "status": "complete",
      "pending": 0,
      "pending_ids": []
    },
    "label_share": {
      "policy_version": "share/1",
      "presets": {
        "question": {
          "n": 33,
          "counted": 5,
          "abstained": 1,
          "share": 0.1563,
          "low": 0.0782,
          "high": 0.2879,
          "receipts": [
            {
              "id": "nk4qy74",
              "text": "Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted)."
            },
            {
              "id": "nk7zp1p",
              "text": "Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted)."
            }
          ],
          "policy_version": "share/1",
          "too_few": false,
          "at_cut": 5,
          "nulls": 0,
          "low_confidence": 1
        },
        "purchase_intent": {
          "n": 33,
          "counted": 2,
          "abstained": 3,
          "share": 0.0667,
          "low": 0.0223,
          "high": 0.1827,
          "receipts": [
            {
              "id": "nk4fn67",
              "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)."
            },
            {
              "id": "nlyjukn",
              "text": "Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted)."
            }
          ],
          "policy_version": "share/1",
          "too_few": false,
          "at_cut": 3,
          "nulls": 0,
          "low_confidence": 3
        },
        "complaint": {
          "n": 33,
          "counted": 3,
          "abstained": 2,
          "share": 0.0968,
          "low": 0.0393,
          "high": 0.2189,
          "receipts": [
            {
              "id": "nk4ee40",
              "text": "Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted)."
            },
            {
              "id": "nlh1o80",
              "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)."
            }
          ],
          "policy_version": "share/1",
          "too_few": false,
          "at_cut": 4,
          "nulls": 0,
          "low_confidence": 2
        },
        "sentiment": {
          "positive": {
            "n": 33,
            "counted": 18,
            "abstained": 5,
            "share": null,
            "low": 0.4875,
            "high": 0.7731,
            "receipts": [
              {
                "id": "nk4bu00",
                "text": "Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted)."
              },
              {
                "id": "nk4fn67",
                "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)."
              }
            ],
            "policy_version": "share/1",
            "too_few": true,
            "at_cut": 18,
            "nulls": 0,
            "low_confidence": 5
          },
          "neutral": {
            "n": 33,
            "counted": 7,
            "abstained": 5,
            "share": null,
            "low": 0.1416,
            "high": 0.4024,
            "receipts": [
              {
                "id": "nk4kecb",
                "text": "Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted)."
              },
              {
                "id": "nk4qy74",
                "text": "Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted)."
              }
            ],
            "policy_version": "share/1",
            "too_few": true,
            "at_cut": 7,
            "nulls": 0,
            "low_confidence": 5
          },
          "negative": {
            "n": 33,
            "counted": 3,
            "abstained": 5,
            "share": 0.1071,
            "low": 0.0436,
            "high": 0.2399,
            "receipts": [
              {
                "id": "nk4ee40",
                "text": "Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted)."
              },
              {
                "id": "nk4exbw",
                "text": "Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted)."
              }
            ],
            "policy_version": "share/1",
            "too_few": false,
            "at_cut": 3,
            "nulls": 0,
            "low_confidence": 5
          }
        }
      }
    },
    "comment_language": {
      "policy_version": "share/1",
      "n": 33,
      "abstained": 1,
      "judged_by": {
        "script": 0,
        "choice": 32
      },
      "shares": {
        "en": {
          "n": 33,
          "counted": 32,
          "abstained": 1,
          "share": 1,
          "low": 0.922,
          "high": 1,
          "receipts": [
            {
              "id": "nk4bu00",
              "text": "Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted)."
            },
            {
              "id": "nk4ee40",
              "text": "Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted)."
            }
          ],
          "policy_version": "share/1",
          "too_few": false
        }
      }
    },
    "comment_recency": {
      "policy_version": "d09-1",
      "n": 33,
      "counted": 33,
      "abstained": 0,
      "share_last_24h": 0,
      "share_later_half": null,
      "too_few": false,
      "stage": "unknown",
      "order": "default",
      "recent_share_is_floor": true,
      "receipts": []
    },
    "dropped": 0
  },
  "credits_used": 5,
  "request_id": "req_example000000",
  "cached": false,
  "pagination": {
    "next_cursor": null,
    "has_more": false,
    "page_size": 33
  },
  "credits_remaining": 9999,
  "source": "captured",
  "captured_at": "2026-10-02T15:39:22.882Z",
  "redacted": true
}

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

API 상세

Reddit Post Comments API는 어떻게 동작하나요

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

메서드

GET

응답 형식

JSON

왜 SocialCrawl인가요

Reddit Post Comments 데이터는 왜 SocialCrawl로 가져올까요

Reddit 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 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"
    }
  }
}
+ 68개 플랫폼
자주 묻는 질문

자주 묻는 질문

API, 요금제, 기능에 대한 질문과 답변입니다.

문의하기
Reddit 게시물의 댓글은 어떻게 가져오나요?
GET /v1/reddit/post/comments에 url 파라미터로 게시물 전체 URL을 담아 호출하면 돼요. 작성자, 본문, 점수, 답글 수, 어워드, 작성 시각이 포함된 댓글 트리 전체를 JSON으로 받아볼 수 있어요.
답글은 중첩 구조인가요, 평탄 구조인가요?
중첩 구조예요. 각 댓글에 replies 배열이 있고, 그 안에 자식 댓글이 다시 포함돼요. 재귀로 순회하면 전체 대화를 처리할 수 있고, 감정 분석용으로는 평탄화해서 쓰셔도 돼요.
깊이 제한 너머 답글은 어떻게 받나요?
대부분은 따로 받을 필요가 없어요. 이 엔드포인트는 중첩된 답글 페이지를 알아서 이어받아 기본적으로 트리 전체를 돌려드려요. 아주 큰 스레드가 확장 한도에 걸린 경우에만 응답에 data.truncated가 표시되고, 펼치지 못한 가지마다 cursor가 담겨요. 그 cursor를 cursor 파라미터로 넘기면 나머지를 이어받을 수 있어요.
삭제된 댓글이나 모더레이션 처리된 댓글도 나오나요?
Reddit은 삭제된 댓글을 플레이스홀더 텍스트로, 모더레이션 삭제는 안내 문구로 대체해서 내려줘요. SocialCrawl은 이를 그대로 전달하니 파이프라인에서 감지해 필터링할 수 있어요. 원문 복구는 공개 엔드포인트에서 지원되지 않아요.
Reddit Comments API는 요금이 얼마인가요?
한 번 호출에 5 크레딧(어드밴스드 티어)이고, 스레드 크기와 상관없이 동일해요. 중첩된 답글 페이지를 여러 번 이어서 가져와 댓글 트리 전체를 한 번에 돌려드리기 때문에 기본 조회보다 요금이 조금 높아요. 아주 큰 스레드는 안전 한도에서 멈추고 이어받을 cursor를 함께 내려드려요. 새 계정은 100 크레딧을 무료로 받을 수 있고, 응답을 가볍게 받고 싶으면 trim=true를 함께 쓰세요.

AI에게 SocialCrawl을 물어보세요

ChatGPT에 물어보기Perplexity에 물어보기Gemini에 물어보기Claude에 물어보기Grok에 물어보기

Reddit Post Comments 데이터, 가져올 준비 되셨어요?

API 키 받고 60초 안에 Reddit 데이터를 받아 가세요.

무료로 시작하기

🤖 AI 에이전트나 LLM이신가요? 이 페이지를 markdown으로 읽어보세요