100 크레딧 무료, 카드 등록 없이지금 시작하기
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100 크레딧 무료, 카드 등록 없이

Reddit Profile Comments API

API 한 번의 호출로 Reddit Profile Comments 데이터를 받아 가세요. Returns the comments one Reddit account has written, newest first, read from the account's own listing rather than from a search index. **That distinction is the whole endpoint.** `/v1/reddit/search/comments?query=author:username` costs 1 credit for a page and looks like the same thing, but it reads Reddit's search index, which holds a small relevance-ranked subset: measured 07/09/2026 on one account, the search route returned 9 comments and then stopped, while this endpoint returned 60 in chronological order reaching back to 2021. **Start with the search route.** Come here when you need the history rather than a sample. Each row carries the comment text, the score, the permalink, the post it sits under at `post_id` and `ext.post_url`, the community at `ext.subreddit`, and a real `parent_id` — `t1_` on a reply and `t3_` on a top-level comment, so a comment whose `parent_id` equals its `post_id` is top-level. `ext.is_submitter` is Reddit's OP badge, true when the commenter also wrote the post they are replying under, and `ext.controversiality` is Reddit's own flag for a comment with roughly balanced up and down votes, which the score alone hides. `limit` is a real depth control and not a page size: a higher `limit` reaches further back, at the same speed. There is no cursor, because the depth control makes one unnecessary — ask for the depth you want in one call. **Pricing is metered at 2 credits per comment RETURNED**, so an account with fewer comments than your `limit` costs less than you asked for. A username that does not exist returns an empty list and costs nothing, and so does a real account that has never commented — this upstream cannot tell them apart, so call `/v1/reddit/profile` when you need to know which it was. When the main source is unavailable, a second source answers the same call with the same fields and the same price; on those rows `comment.text` is Reddit's own markdown, so a link reads `[text](url)`. A call with `before` has no second source and returns an error to retry.

2026년 10월 업데이트SocialCrawl 팀이 직접 관리해요

계정 하나가 쓴 댓글을 최신순으로 돌려줍니다. 검색 색인이 아니라 계정의 댓글 목록에서 직접 읽어옵니다. 각 댓글에는 본문, 점수, permalink, 달린 게시물, ext.subreddit의 커뮤니티, 그리고 실제 parent_id가 붙습니다.

표본이 아니라 실제 댓글 이력 전체가 필요할 때 쓰세요. 먼저 search/comments에 query=author:이름을 넣어 보세요. 페이지당 1크레딧이지만 검색 색인을 읽기 때문에 결과가 훨씬 적습니다.

69개 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

Profile Comments API로 무엇을 할 수 있을까요

Profile 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/profile/comments?handle=spez"
import requests

response = requests.get(
    "https://www.socialcrawl.dev/v1/reddit/profile/comments",
    params={
    'handle': 'spez',
    },
    headers={"x-api-key": "YOUR_API_KEY"},
)

data = response.json()
const response = await fetch(
  "https://www.socialcrawl.dev/v1/reddit/profile/comments?handle=spez",
  {
    headers: { "x-api-key": "YOUR_API_KEY" },
  },
);

const data = await response.json();

파라미터

파라미터필수설명
handle예Reddit username without the u/ prefix. Case-insensitive.
limit아니오How many comments to return, 1-100, default 25. This is a depth control, not a page size: a higher limit reaches further back into the account's history at the same speed.
before아니오Only return comments older than this date (YYYY-MM-DD). Use it to walk a long history in windows instead of raising limit.
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 Profile 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": "youtube",
  "endpoint": "/v1/youtube/video/comments",
  "data": {
    "items": [
      {
        "comment": {
          "id": "Ugzge340dBgB75hWBm54AaABAg",
          "url": null,
          "parent_id": null,
          "post_id": "dQw4w9WgXcQ",
          "text": "Sample comment text (redacted).",
          "author": {
            "username": "user_607bca",
            "display_name": "user_607bca",
            "avatar_url": "https://example.com/avatars/user_b3bde6.png",
            "verified": null
          },
          "engagement": {
            "likes": 322497,
            "replies": 1000
          },
          "flags": {
            "pinned": null,
            "deleted": false
          },
          "published_at": "2025-04-22T19:05:08.000Z",
          "ext": {
            "replies_token": "sc2.eyJzIjoiYSIsImMiOiJVZ3pnZTM0MGRCZ0I3NWhXQm01NEFhQUJBZyJ9",
            "updated_at": "2025-04-22T19:05:08Z",
            "author_channel_id": "user_0faa89",
            "author_url": "https://example.com/user_fa30a8",
            "viewer_rating": "Sample comment text (redacted).",
            "text_original": "Sample comment text (redacted).",
            "preview_replies": [
              {
                "id": "Ugzge340dBgB75hWBm54AaABAg.AHE8_QAWJx9AHE9eIiztxR",
                "channelId": "user_b70959",
                "videoId": "dQw4w9WgXcQ",
                "textDisplay": "Sample comment text (redacted).",
                "textOriginal": "Sample comment text (redacted).",
                "parentId": "Ugzge340dBgB75hWBm54AaABAg",
                "authorDisplayName": "user_a07ce6",
                "authorProfileImageUrl": "https://example.com/avatars/user_b7fd7d.png",
                "authorChannelUrl": "https://example.com/user_7ab559",
                "authorChannelId": {
                  "value": "user_5afaba"
                },
                "canRate": true,
                "viewerRating": "Sample comment text (redacted).",
                "likeCount": 7573,
                "publishedAt": "2025-04-22T19:14:32Z",
                "updatedAt": "2025-04-22T19:14:32Z"
              },
              {
                "id": "Ugzge340dBgB75hWBm54AaABAg.AHE8_QAWJx9AHEAB_-JmDA",
                "channelId": "user_b70959",
                "videoId": "dQw4w9WgXcQ",
                "textDisplay": "Sample comment text (redacted).",
                "textOriginal": "Sample comment text (redacted).",
                "parentId": "Ugzge340dBgB75hWBm54AaABAg",
                "authorDisplayName": "user_d8b3d6",
                "authorProfileImageUrl": "https://example.com/avatars/user_2ece01.png",
                "authorChannelUrl": "https://example.com/user_7a3f35",
                "authorChannelId": {
                  "value": "user_da87da"
                },
                "canRate": true,
                "viewerRating": "Sample comment text (redacted).",
                "likeCount": 3180,
                "publishedAt": "2025-04-22T19:19:13Z",
                "updatedAt": "2025-04-22T19:19:13Z"
              }
            ]
          }
        },
        "computed": {
          "language": "en",
          "labels": {
            "sentiment": {
              "level": 3,
              "score_0_1": 0.85,
              "confidence": 0.61
            },
            "question": {
              "p": 0.03
            },
            "purchase_intent": {
              "p": 0.02
            },
            "complaint": {
              "p": 0.04
            }
          }
        }
      },
      {
        "comment": {
          "id": "UgzjClLu_KHsDVWheGx4AaABAg",
          "url": null,
          "parent_id": null,
          "post_id": "dQw4w9WgXcQ",
          "text": "Sample comment text (redacted).",
          "author": {
            "username": "user_f90324",
            "display_name": "user_f90324",
            "avatar_url": "https://example.com/avatars/user_191ddb.png",
            "verified": null
          },
          "engagement": {
            "likes": 1,
            "replies": 0
          },
          "flags": {
            "pinned": null,
            "deleted": false
          },
          "published_at": "2026-10-02T15:39:20.000Z",
          "ext": {
            "replies_token": "sc2.eyJzIjoiYSIsImMiOiJVZ3pqQ2xMdV9LSHNEVldoZUd4NEFhQUJBZyJ9",
            "updated_at": "2026-10-02T15:39:20Z",
            "author_channel_id": "user_121069",
            "author_url": "https://example.com/user_ec3ca5",
            "viewer_rating": "Sample comment text (redacted).",
            "text_original": "Sample comment text (redacted)."
          }
        },
        "computed": {
          "language": "en",
          "labels": {
            "sentiment": {
              "level": 3,
              "score_0_1": 0.76,
              "confidence": 0.8
            },
            "question": {
              "p": 0.02
            },
            "purchase_intent": {
              "p": 0.02
            },
            "complaint": {
              "p": 0.03
            }
          }
        }
      }
    ],
    "next_cursor": "sc2.eyJzIjoiYSIsImMiOiJzYzEuZXlKaklqb2lXakpXTUZneU5XeGtNbFo2WkVZNWJXRllTbnBrUXpCMFVUSmtibE5YWkVKVlZscEhUakphVTFRd1NrcFNhMDVPV2pKa1NGRlZSbFJSYkVad1drVnNRMW93U2taYU1WWktZVlZPUWxkVlJrTlRWVnBFVXpKa2JsSXdSa0pWTUVwU1lWVm9TbEZ0WkVKU1YyUldVMWMxY0ZGV2JFSlJhMnhIVVRCc2Nsb3daRUpSVjJ4RldqSTVUbEV3ZEd4YU1UZzFWbFZrUmxNeWF6Rk9SWEJDVWtaV1FsRnNiRUpWVVQwOUlpd2ljeUk2V3lKVlozcG5aVE0wTUdSQ1owSTNOV2hYUW0wMU5FRmhRVUpCWnlJc0lsVm5lbXBEYkV4MVgwdEljMFJXVjJobFIzZzBRV0ZCUWtGbklsMTkifQ",
    "total": null,
    "labels": {
      "presets": [
        "sentiment",
        "question"
      ],
      "rows": 2,
      "labelled": 2,
      "cached": 1,
      "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": 2,
          "counted": 0,
          "abstained": 0,
          "share": null,
          "low": 0,
          "high": 0.575,
          "receipts": [],
          "policy_version": "share/1",
          "too_few": true,
          "at_cut": 0,
          "nulls": 0,
          "low_confidence": 0
        },
        "purchase_intent": {
          "n": 2,
          "counted": 0,
          "abstained": 0,
          "share": null,
          "low": 0,
          "high": 0.575,
          "receipts": [],
          "policy_version": "share/1",
          "too_few": true,
          "at_cut": 0,
          "nulls": 0,
          "low_confidence": 0
        },
        "complaint": {
          "n": 2,
          "counted": 0,
          "abstained": 0,
          "share": null,
          "low": 0,
          "high": 0.575,
          "receipts": [],
          "policy_version": "share/1",
          "too_few": true,
          "at_cut": 0,
          "nulls": 0,
          "low_confidence": 0
        },
        "sentiment": {
          "positive": {
            "n": 2,
            "counted": 2,
            "abstained": 0,
            "share": null,
            "low": 0.425,
            "high": 1,
            "receipts": [
              {
                "id": "Ugzge340dBgB75hWBm54AaABAg",
                "text": "Sample comment text (redacted)."
              },
              {
                "id": "UgzjClLu_KHsDVWheGx4AaABAg",
                "text": "Sample comment text (redacted)."
              }
            ],
            "policy_version": "share/1",
            "too_few": true,
            "at_cut": 2,
            "nulls": 0,
            "low_confidence": 0
          },
          "neutral": {
            "n": 2,
            "counted": 0,
            "abstained": 0,
            "share": null,
            "low": 0,
            "high": 0.575,
            "receipts": [],
            "policy_version": "share/1",
            "too_few": true,
            "at_cut": 0,
            "nulls": 0,
            "low_confidence": 0
          },
          "negative": {
            "n": 2,
            "counted": 0,
            "abstained": 0,
            "share": null,
            "low": 0,
            "high": 0.575,
            "receipts": [],
            "policy_version": "share/1",
            "too_few": true,
            "at_cut": 0,
            "nulls": 0,
            "low_confidence": 0
          }
        }
      }
    },
    "comment_language": {
      "policy_version": "share/1",
      "n": 2,
      "abstained": 0,
      "judged_by": {
        "script": 0,
        "choice": 2
      },
      "shares": {
        "en": {
          "n": 2,
          "counted": 2,
          "abstained": 0,
          "share": null,
          "low": 0.425,
          "high": 1,
          "receipts": [
            {
              "id": "Ugzge340dBgB75hWBm54AaABAg",
              "text": "Sample comment text (redacted)."
            },
            {
              "id": "UgzjClLu_KHsDVWheGx4AaABAg",
              "text": "Sample comment text (redacted)."
            }
          ],
          "policy_version": "share/1",
          "too_few": true
        }
      }
    },
    "comment_recency": {
      "policy_version": "d09-1",
      "n": 2,
      "counted": 2,
      "abstained": 0,
      "share_last_24h": 0.5,
      "share_later_half": null,
      "too_few": true,
      "stage": "unknown",
      "order": "top",
      "recent_share_is_floor": true,
      "receipts": [
        {
          "id": "UgzjClLu_KHsDVWheGx4AaABAg",
          "text": "Sample comment text (redacted)."
        }
      ]
    },
    "dropped": 0
  },
  "credits_used": 1,
  "credits_remaining": 9999,
  "request_id": "req-8Kq2ZmR4vT9xLb3P",
  "cached": false,
  "pagination": {
    "next_cursor": "sc.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",
    "has_more": true,
    "page_size": 2
  },
  "redacted": true
}

YouTube API에서 가져온 예시예요. 모든 SocialCrawl 엔드포인트가 똑같은 통합 스키마를 돌려주기 때문에, Reddit Profile Comments 응답도 같은 필드로 구성돼요.

API 상세

Reddit Profile 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 Profile 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 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"
    }
  }
}
+ 69개 플랫폼
자주 묻는 질문

자주 묻는 질문

API, 요금제, 기능에 대한 질문과 답변입니다.

문의하기
한 계정의 댓글 기록은 어떻게 받나요?
GET /v1/reddit/profile/comments에 사용자 이름을 담아 호출하면 돼요. 검색 색인이 아니라 계정 자체의 목록에서 읽어 오기 때문에, 최신순으로 댓글 본문, 점수, permalink, 달린 글 정보가 함께 와요.
author: 연산자로 검색하는 것과 무엇이 다른가요?
표본만 필요하면 1 credit짜리 /v1/reddit/search/comments?query=author:이름부터 써 보세요. 그쪽은 검색 색인이라 일부만 담겨요. 한 계정에서 재어 보니 검색은 9개에서 끝났고 이 엔드포인트는 몇 해 전까지 60개를 돌려줬어요.
더 오래된 댓글까지 받으려면 어떻게 하나요?
limit을 올리면 돼요. 페이지 크기가 아니라 깊이 조절값이라, 값을 키우면 같은 속도로 더 예전까지 닿고 최대 100까지 넣을 수 있어요. 커서는 없고, 그보다 더 가려면 받은 가장 오래된 날짜를 before에 넣으세요.
댓글 기록 API 요금은 얼마인가요?
돌려받은 댓글 하나당 2 크레딧인 종량제예요. limit의 두 배를 미리 잡아 두고 실제로 온 댓글 수만큼만 정산해요. 댓글이 limit보다 적은 계정은 그만큼만 내고, 댓글이 없으면 0크레딧이에요.
최상위 댓글과 대댓글을 구분할 수 있나요?
parent_id로 구분할 수 있어요. 최상위 댓글은 t3_로, 대댓글은 t1_로 시작해서 parent_id가 post_id와 같으면 스레드 맨 위 댓글이에요. ext.is_submitter가 true면 글 작성자가 단 댓글이에요.

AI에게 SocialCrawl을 물어보세요

Reddit Profile Comments 데이터, 가져올 준비 되셨어요?

API 키 받고 60초 안에 Reddit 데이터를 받아 가세요.

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