Reddit Profile Comments API
Scrape Reddit Profile Comments data with one API call. 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.
Last updated October 2026Maintained by the SocialCrawl team
Returns an account's own comment history, newest first, each with the text, score, permalink, parent_id, the post it sits under and ext.subreddit.
Use it when you need a real comment history rather than a sample. Try search/comments with query=author:name first: 1 credit a page, but far fewer rows.
Searching 69 platforms in parallel
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 SearchTikTok·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 SearchTikTok·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 SearchTikTok·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 SearchWhat can you do with the Profile Comments API?
The Profile Comments endpoint gives you structured Reddit data with computed fields in a single request. No scraping infrastructure to build or maintain.
Example Request
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();Parameters
| Parameter | Required | Description |
|---|---|---|
| handle | Yes | Reddit username without the u/ prefix. Case-insensitive. |
| limit | No | How 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. |
| before | No | Only return comments older than this date (YYYY-MM-DD). Use it to walk a long history in windows instead of raising limit. |
| since | No | Only rows published on or after this date: YYYY-MM-DD (midnight UTC) or an ISO 8601 timestamp. Rows older than it are left off each page. This list is not in date order, so the walk does not stop at the date: keep following `next_cursor`, and each page costs what a page costs even when every row on it is filtered out. A row with no date is kept. `published_after`, `start_date`, `from_date`, `publish_time` (`yesterday`, `this-week`, `this-month`, `last-3-months`, `last-6-months`) and `max_age_days` are accepted and applied as `since`. |
| until | No | 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`. |
What does the Reddit Profile Comments API return?
Every response follows one unified schema. Here is a real, unmodified response body, so you can see the exact fields you get back before spending a credit.
Example response
{
"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
}Example captured from the YouTube API. Every SocialCrawl endpoint returns this same unified schema, so your Reddit Profile Comments response has the same fields.
How does the Reddit Profile Comments API work?
Send a GET request with your API key and get back clean, structured JSON in our unified schema. Supported computed fields are populated when the source provides the required inputs.
Method
GET
Response
JSON
How do you scrape social media data in seconds?
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Query 69 platforms with identical response structures. Write your integration once.
Computed fields, not just scraped
When an endpoint supports these metrics and the source provides the required inputs, the normalized record includes engagement_rate, estimated_reach, content_category, and language. Ready to use.
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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(){
"success": true,
"platform": "tiktok",
"data": {
"author": {
"username": "charlidamelio",
"followers": 152400000
},
"engagement": {
"likes": 12400000000,
"engagement_rate": 0.087
},
"metadata": {
"language": "en",
"content_category": "lifestyle"
}
}
}Have a question? We got answers
Find answers to frequently asked questions about SocialCrawl's API, pricing, and capabilities.
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