Facebook Post Comments API
Scrape Facebook Post Comments data with one API call. Returns a list of comments on a specific Facebook post. Each comment includes the author name, comment text, like count, reply count, and creation timestamp.
Last updated October 2026Maintained by the SocialCrawl team
Returns comments on a Facebook post, each with the commenter's name, comment text, like count, reply count, and creation time.
Use it to read a post's discussion; it also returns the feedback_id and expansion_token that post/comment/replies needs.
Searching 68 platforms in parallel
What can you do with the Post Comments API?
The Post Comments endpoint gives you structured Facebook 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/facebook/post/comments?url=https%3A%2F%2Fwww.facebook.com%2FMeta%2Fvideos%2Fa-slightly-life-changing-story%2F1459847961114516%2F&label=purchase_intent"import requests
response = requests.get(
"https://www.socialcrawl.dev/v1/facebook/post/comments",
params={
'url': 'https://www.facebook.com/Meta/videos/a-slightly-life-changing-story/1459847961114516/',
'label': 'purchase_intent',
},
headers={"x-api-key": "YOUR_API_KEY"},
)
data = response.json()const response = await fetch(
"https://www.socialcrawl.dev/v1/facebook/post/comments?url=https%3A%2F%2Fwww.facebook.com%2FMeta%2Fvideos%2Fa-slightly-life-changing-story%2F1459847961114516%2F&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 | No | Full URL of the Facebook post to fetch comments for |
| feedback_id | No | Using feedback_id (instead of url) will *really* speed up the request. You can get the feedback_id when you make a request to /v1/facebook/post. |
| cursor | No | Cursor to get more comments. Get 'cursor' from previous response. |
| 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 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 Facebook Post 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": "facebook",
"endpoint": "/v1/facebook/post/comments",
"data": {
"items": [
{
"comment": {
"id": "Y29tbWVudDo1NjMwNjMzMjg1ODg1OTdfNTMyNTQ3NDgxNTk0OTk2",
"url": null,
"parent_id": null,
"post_id": "563063328588597",
"text": "Sample comment text (redacted).",
"author": {
"username": "user_add51c",
"display_name": "user_3d0e68",
"avatar_url": "https://example.com/avatars/user_f59eee.png",
"verified": null
},
"engagement": {
"likes": 0,
"replies": 3
},
"flags": {
"pinned": null,
"deleted": false
},
"published_at": "2022-04-13T02:26:17.000Z",
"ext": {
"feedback_id": "ZmVlZGJhY2s6NTYzMDYzMzI4NTg4NTk3XzUzMjU0NzQ4MTU5NDk5Ng==",
"expansion_token": "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).",
"reaction_counts": null
}
},
"computed": {
"language": null,
"labels": {
"sentiment": {
"level": 3,
"score_0_1": 0.77,
"confidence": 0.94
},
"question": {
"p": 0.02
},
"purchase_intent": {
"p": 0.02
},
"complaint": {
"p": 0.02
}
}
}
},
{
"comment": {
"id": "Y29tbWVudDo1NjMwNjMzMjg1ODg1OTdfNTcwNjY2Nzk0NDk0OTE3",
"url": null,
"parent_id": null,
"post_id": "563063328588597",
"text": "Sample comment text (redacted).",
"author": {
"username": "user_c5097a",
"display_name": "user_edb910",
"avatar_url": "https://example.com/avatars/user_606f32.png",
"verified": null
},
"engagement": {
"likes": 0,
"replies": 1
},
"flags": {
"pinned": null,
"deleted": false
},
"published_at": "2022-04-13T04:09:36.000Z",
"ext": {
"feedback_id": "ZmVlZGJhY2s6NTYzMDYzMzI4NTg4NTk3XzU3MDY2Njc5NDQ5NDkxNw==",
"expansion_token": "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).",
"reaction_counts": null
}
},
"computed": {
"language": null,
"labels": {
"sentiment": {
"level": 4,
"score_0_1": 1,
"confidence": 1
},
"question": {
"p": 0.02
},
"purchase_intent": {
"p": 0.02
},
"complaint": {
"p": 0.02
}
}
}
}
],
"next_cursor": "sc2.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",
"total": null,
"labels": {
"presets": [
"sentiment",
"question"
],
"rows": 10,
"labelled": 10,
"cached": 10,
"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": 10,
"counted": 2,
"abstained": 0,
"share": null,
"low": 0.0686,
"high": 0.4592,
"receipts": [
{
"id": "Y29tbWVudDo1NjMwNjMzMjg1ODg1OTdfNTcwNjk2MzY3ODI1Mjkz",
"text": "Sample comment text (redacted)."
},
{
"id": "Y29tbWVudDo1NjMwNjMzMjg1ODg1OTdfNTcyODE1MzMwOTQ2NzMw",
"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": 2,
"nulls": 0,
"low_confidence": 0
},
"purchase_intent": {
"n": 10,
"counted": 0,
"abstained": 0,
"share": 0,
"low": 0,
"high": 0.2129,
"receipts": [],
"policy_version": "share/1",
"too_few": false,
"at_cut": 0,
"nulls": 0,
"low_confidence": 0
},
"complaint": {
"n": 10,
"counted": 2,
"abstained": 0,
"share": null,
"low": 0.0686,
"high": 0.4592,
"receipts": [
{
"id": "Y29tbWVudDo1NjMwNjMzMjg1ODg1OTdfNTcyNDQ5OTM0MzE2NjAz",
"text": "Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted). Sample comment text (redacted)."
},
{
"id": "Y29tbWVudDo1NjMwNjMzMjg1ODg1OTdfNTcyODE1MzMwOTQ2NzMw",
"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": 2,
"nulls": 0,
"low_confidence": 0
},
"sentiment": {
"positive": {
"n": 10,
"counted": 5,
"abstained": 1,
"share": null,
"low": 0.3035,
"high": 0.782,
"receipts": [
{
"id": "Y29tbWVudDo1NjMwNjMzMjg1ODg1OTdfNTMyNTQ3NDgxNTk0OTk2",
"text": "Sample comment text (redacted)."
},
{
"id": "Y29tbWVudDo1NjMwNjMzMjg1ODg1OTdfNTcwNjY2Nzk0NDk0OTE3",
"text": "Sample comment text (redacted)."
}
],
"policy_version": "share/1",
"too_few": true,
"at_cut": 5,
"nulls": 0,
"low_confidence": 1
},
"neutral": {
"n": 10,
"counted": 2,
"abstained": 1,
"share": null,
"low": 0.0765,
"high": 0.4964,
"receipts": [
{
"id": "Y29tbWVudDo1NjMwNjMzMjg1ODg1OTdfNTcwNjk2MzY3ODI1Mjkz",
"text": "Sample comment text (redacted)."
},
{
"id": "Y29tbWVudDo1NjMwNjMzMjg1ODg1OTdfNTcyODE1MzMwOTQ2NzMw",
"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": 2,
"nulls": 0,
"low_confidence": 1
},
"negative": {
"n": 10,
"counted": 2,
"abstained": 1,
"share": null,
"low": 0.0765,
"high": 0.4964,
"receipts": [
{
"id": "Y29tbWVudDo1NjMwNjMzMjg1ODg1OTdfNTcxMjE0MDU0NDQwMTkx",
"text": "Sample comment text (redacted)."
},
{
"id": "Y29tbWVudDo1NjMwNjMzMjg1ODg1OTdfNTcyNDQ5OTM0MzE2NjAz",
"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": 2,
"nulls": 0,
"low_confidence": 1
}
}
}
},
"comment_language": {
"policy_version": "share/1",
"n": 10,
"abstained": 0,
"judged_by": {
"script": 0,
"choice": 10
},
"shares": {
"en": {
"n": 10,
"counted": 10,
"abstained": 0,
"share": 1,
"low": 0.7871,
"high": 1,
"receipts": [
{
"id": "Y29tbWVudDo1NjMwNjMzMjg1ODg1OTdfNTMyNTQ3NDgxNTk0OTk2",
"text": "Sample comment text (redacted)."
},
{
"id": "Y29tbWVudDo1NjMwNjMzMjg1ODg1OTdfNTcwNjY2Nzk0NDk0OTE3",
"text": "Sample comment text (redacted)."
}
],
"policy_version": "share/1",
"too_few": false
}
}
},
"comment_recency": {
"policy_version": "d09-1",
"n": 10,
"counted": 10,
"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": 1,
"request_id": "req_example000000",
"cached": false,
"pagination": {
"next_cursor": "sc.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",
"has_more": true,
"page_size": 10
},
"credits_remaining": 9999,
"source": "captured",
"captured_at": "2026-10-02T15:36:44.338Z",
"redacted": true
}Live sample illustrating the unified response shape. Field values reflect the record you query.
How does the Facebook Post 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?
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(){
"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.
Contact usHow do I get comments from a Facebook post?
What is feedback_id and why should I use it?
How many comments can I paginate through?
Are comment replies included?
Can I use this endpoint for sentiment analysis?
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