100 free credits. No credit card required
YouTube Video Comments API
Scrape YouTube Video Comments data with one API call. Returns a list of comments on a specific YouTube video. Each comment includes the author name, comment text, like count, reply count, and an exact per-second publish timestamp. For a date-window pull (say, the last two years of comments), request `order=newest` and paginate: rows arrive newest-first on `comment.published_at` and each next page continues strictly older with no overlap, so keep the rows inside your window and stop paging once a page's oldest row falls before it. There is no server-side date parameter because YouTube exposes none for comments: a filter here would walk the same pages at the same cost, so the cutoff belongs client-side where it can also stop the walk. One caveat for that walk: the first row of the first page can be the video's pinned comment regardless of `order`, so filter rows by timestamp rather than terminating at the first out-of-window row.
Last updated October 2026Maintained by the SocialCrawl team
Returns comments on a video, each with the author name, comment text, like count, reply count, and publish timestamp.
Use it for a video's top-level comments, then pass the reply token it returns to video/comment/replies to open a single thread.
Searching 68 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 Search
TikTok·Instagram·YouTube·Facebook·X·LinkedIn·Reddit·Threads·Pinterest·Twitch·Truth Social·Snapchat·Kick·Bluesky·Kwai·Rumble·Spotify·Apple Music·TikTok Shop·Amazon Shop·Google Shopping·Trustpilot·TripAdvisor·Yelp·Linktree·Komi·Pillar·lnk.bio·Facebook Ads·Google Ads·LinkedIn Ads·Google Search·Google News·Finance·Polymarket·Tavily·Hacker News·GitHub·Perplexity·Naver·Utility·Universal Search·TikTok·Instagram·YouTube·Facebook·X·LinkedIn·Reddit·Threads·Pinterest·Twitch·Truth Social·Snapchat·Kick·Bluesky·Kwai·Rumble·Spotify·Apple Music·TikTok Shop·Amazon Shop·Google Shopping·Trustpilot·TripAdvisor·Yelp·Linktree·Komi·Pillar·lnk.bio·Facebook Ads·Google Ads·LinkedIn Ads·Google Search·Google News·Finance·Polymarket·Tavily·Hacker News·GitHub·Perplexity·Naver·Utility·Universal Search
TikTok·Instagram·YouTube·Facebook·X·LinkedIn·Reddit·Threads·Pinterest·Twitch·Truth Social·Snapchat·Kick·Bluesky·Kwai·Rumble·Spotify·Apple Music·TikTok Shop·Amazon Shop·Google Shopping·Trustpilot·TripAdvisor·Yelp·Linktree·Komi·Pillar·lnk.bio·Facebook Ads·Google Ads·LinkedIn Ads·Google Search·Google News·Finance·Polymarket·Tavily·Hacker News·GitHub·Perplexity·Naver·Utility·Universal Search·TikTok·Instagram·YouTube·Facebook·X·LinkedIn·Reddit·Threads·Pinterest·Twitch·Truth Social·Snapchat·Kick·Bluesky·Kwai·Rumble·Spotify·Apple Music·TikTok Shop·Amazon Shop·Google Shopping·Trustpilot·TripAdvisor·Yelp·Linktree·Komi·Pillar·lnk.bio·Facebook Ads·Google Ads·LinkedIn Ads·Google Search·Google News·Finance·Polymarket·Tavily·Hacker News·GitHub·Perplexity·Naver·Utility·Universal Search
TikTok·Instagram·YouTube·Facebook·X·LinkedIn·Reddit·Threads·Pinterest·Twitch·Truth Social·Snapchat·Kick·Bluesky·Kwai·Rumble·Spotify·Apple Music·TikTok Shop·Amazon Shop·Google Shopping·Trustpilot·TripAdvisor·Yelp·Linktree·Komi·Pillar·lnk.bio·Facebook Ads·Google Ads·LinkedIn Ads·Google Search·Google News·Finance·Polymarket·Tavily·Hacker News·GitHub·Perplexity·Naver·Utility·Universal Search·TikTok·Instagram·YouTube·Facebook·X·LinkedIn·Reddit·Threads·Pinterest·Twitch·Truth Social·Snapchat·Kick·Bluesky·Kwai·Rumble·Spotify·Apple Music·TikTok Shop·Amazon Shop·Google Shopping·Trustpilot·TripAdvisor·Yelp·Linktree·Komi·Pillar·lnk.bio·Facebook Ads·Google Ads·LinkedIn Ads·Google Search·Google News·Finance·Polymarket·Tavily·Hacker News·GitHub·Perplexity·Naver·Utility·Universal Search
TikTok·Instagram·YouTube·Facebook·X·LinkedIn·Reddit·Threads·Pinterest·Twitch·Truth Social·Snapchat·Kick·Bluesky·Kwai·Rumble·Spotify·Apple Music·TikTok Shop·Amazon Shop·Google Shopping·Trustpilot·TripAdvisor·Yelp·Linktree·Komi·Pillar·lnk.bio·Facebook Ads·Google Ads·LinkedIn Ads·Google Search·Google News·Finance·Polymarket·Tavily·Hacker News·GitHub·Perplexity·Naver·Utility·Universal SearchYouTube API
What can you do with the Video Comments API?
The Video Comments endpoint gives you structured YouTube 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/youtube/video/comments?url=https%3A%2F%2Fwww.youtube.com%2Fwatch%3Fv%3DdQw4w9WgXcQ&label=purchase_intent"import requests
response = requests.get(
"https://www.socialcrawl.dev/v1/youtube/video/comments",
params={
'url': 'https://www.youtube.com/watch?v=dQw4w9WgXcQ',
'label': 'purchase_intent',
},
headers={"x-api-key": "YOUR_API_KEY"},
)
data = response.json()const response = await fetch(
"https://www.socialcrawl.dev/v1/youtube/video/comments?url=https%3A%2F%2Fwww.youtube.com%2Fwatch%3Fv%3DdQw4w9WgXcQ&label=purchase_intent",
{
headers: { "x-api-key": "YOUR_API_KEY" },
},
);
const data = await response.json();Parameters worth sending
label=purchase_intentMarks each comment that shows buying intent, at no extra credits; sentiment, question and complaint are free too.
Parameters
| Parameter | Required | Description |
|---|---|---|
| url | Yes | Full URL of the YouTube video to fetch comments for |
| continuationToken | No | Continuation token to get more comments. Get 'continuationToken' from previous response. |
| order | No | Order of comments: 'top' (default, YouTube's relevance ranking) or 'newest' (exact newest-first on `comment.published_at`; each next page continues strictly older with no overlap: the lane for date-window and recency pulls). (top | newest) |
| searchTerm | No | Filter comments to those containing this search term. |
| format | No | Text format for comment bodies: 'html' (default) or 'plainText'. (html | plainText) |
| max_results | No | Comments per page, 1-100. The default page is already 100, so set this only to shrink a page; out-of-range values are rejected with a free 400 rather than degrading the response. |
| channel_id | No | YouTube channel id to fetch channel-level community comments for (instead of a video's comments). |
| label | No | Optional 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. |
| exclude | No | Optional 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. |
| judgments | No | Optional, on (the default) or off. By default every row gains free SocialCrawl judgments (computed.labels, and computed.relevance on search endpoints), reported in data.labels (mode default) and data.relevance (origin default), each with a status (complete, partial or skipped) and pending: the rows still being judged when the page was sent, which carry null now and are filled on your next call or cached read. Default judgments never add credits, never change an existing field, and never drop or reorder a row. off returns the page exactly as before, with none of those keys. label=none does the same. (on | off) |
| dry_run | No | Optional. When 1, return a cost preview for this labelled or relevance-filtered request without fetching the page or judging any row. data.estimate reports rows_expected, rows_cached, label_credits_min, label_credits_max and base_credits. 0 credits charged. (1) |
| label_evidence | No | Optional, only with label=. When 1, every labelled row also carries computed.labels_evidence.<preset> = { quote, sentence_index }: the sentence in the row that most clearly shows the label, copied verbatim. Absent or null when no single sentence shows it. (1) |
| fit | No | Optional. When goal, keep the rows and fields needed for the goal you pass in goal= (plus any that are uncertain, and the first and last), and replace the rest with a stub. data.held_back lists the held ids and a recall id that re-reads the full page from cache at no extra charge. Without this param the page is unchanged. (goal) |
| goal | No | Required by fit=goal. What you are trying to do, in your own words, up to 300 characters. |
| fit_tokens | No | Optional, only with fit=goal. Soft cap on how much of the page to keep, in tokens. Uncertain blocks and the first and last block are kept even if they exceed it. |
| 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 the page, and the page that reaches one ends the walk: `next_cursor` is not returned and `pagination.stopped_at` is `since`. Sending it sets the newest-first sort shown in this endpoint's sort parameter (any other sort value is a free 400). The page still costs what a page costs, so you pay for the pages you walk and no more. A row with no date is kept. `published_after`, `start_date`, `from_date`, `publish_time` (`yesterday`, `this-week`, `this-month`, `last-3-months`, `last-6-months`) and `max_age_days` are accepted and applied as `since`. |
| until | 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`. |
Example Response
What does the YouTube Video 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,
"request_id": "req_example000000",
"cached": false,
"pagination": {
"next_cursor": "sc.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",
"has_more": true,
"page_size": 2
},
"credits_remaining": 9999,
"source": "captured",
"captured_at": "2026-10-02T15:41:15.579Z",
"redacted": true
}Live sample illustrating the unified response shape. Field values reflect the record you query.
API Details
How does the YouTube Video 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
Developer First
How do you scrape social media data in seconds?
The fastest social media scraping API for developers. Scrape profiles, posts, comments, and analytics from 68 platforms covering 10B+ monthly active users.
One schema, every platform
Query 68 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.
See your data before you code
Visual Data Explorer. Paste any URL, get rich result cards, sortable tables, CSV export.
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"
}
}
}FAQ
Have a question? We got answers
Find answers to frequently asked questions about SocialCrawl's API, pricing, and capabilities.
Contact usHow do I scrape comments from a YouTube video?
Send a GET request to /v1/youtube/video/comments with the video URL in the url parameter. The response includes author name, comment text, like count, reply count, and publish timestamp for each comment.
Can I sort comments by top or newest?
Yes. Pass order=top for the most-liked comments first, or order=newest for reverse-chronological order. Default is top, which matches YouTube's default UI sort.
How do I paginate through every comment?
Each response returns a continuationToken. Pass it as continuationToken=... on the next call to get the next page. Keep going until the token is empty, no total-count cap.
How do I get replies to a specific comment?
Every comment with replies exposes a repliesContinuationToken. Pass it to /v1/youtube/video/comment/replies to fetch the full reply thread with author, text, likes, and publish date.
Is this good for YouTube sentiment analysis?
Yes. You get clean comment text with author and engagement counts, ready to feed into an LLM or classifier. Batch it with the video endpoint to pair comments with video metadata.
Ask AI about SocialCrawl
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