Facebook Comments Scraper

Facebook Comments Scraper

Facebook Comments Scraper is a production‑ready Facebook comments extractor that collects top‑level comments and nested replies from public Facebook posts and videos at scale. It helps marketers, developers, data analysts, and researchers scrape Facebook comments reliably, then download Facebook comments for analysis, reporting, or moderation. With sort controls and limits, this Facebook post comments scraper streamlines social listening and lets you automate Facebook comment collection across multiple URLs.

What data / output can you get?

Use this Facebook comments scraping tool to capture structured fields from each comment. Below are the primary output fields pushed to the dataset.

Field	Description	Example value
full_url	Full Facebook post URL for the source	https://www.facebook.com/SomePage/posts/1234567890
url_key	Short identifier derived from the post URL	1234567890
text	Comment text content	Love this announcement!
profileName	Comment author’s display name	Jane Doe
profileId	Facebook ID of the author	1000123456789
date	ISO‑8601 timestamp (UTC) when the comment was created	2026-03-28T06:09:00+00:00
likesCount	Number of reactions on the comment (string)	7
commentsCount	Number of replies to the comment (integer)	2
commentUrl	Permalink to the comment thread	https://www.facebook.com/.../comment/987654321
id	Comment node ID	987654321
facebookId	Legacy FBID for the comment	9876543210
reply	Array of reply objects (same structure as comments)	[ { "id": "111", "text": "Thanks!" } ]

Bonus/optional fields (when available): profilePicture, profileUrl, feedbackId, facebookUrl, threadingDepth, expansionToken, pageAdLibrary. You can export Facebook comments to CSV or JSON from the Apify dataset.

Key features

• ⚡️ Bold-scale extraction & batching
  Process multiple Facebook post/video URLs in one run to scrape Facebook comments at scale without manual effort.

• 🧵 Comments + replies (threaded)
  Fetches top‑level comments and nested replies, returning a clean structure for analysis and moderation workflows.

• 🧭 Flexible sorting controls
  Choose how to order comments via commentsSortOrder: most_relevant, newest, or all (original order) to fit your reporting needs.

• 🛡️ Residential proxy automation
  Always uses Apify Residential proxies under the hood for reliability on Facebook. The proxyConfiguration input is ignored by design to prevent blocking.

• 🧪 Robust retries & stability
  Built with request retries and backoff to mitigate transient failures and ensure consistent Facebook comments API‑style extraction.

• 💾 Analytics‑ready outputs
  Structured JSON output for easy processing. Download Facebook comments to CSV/JSON directly from the dataset.

• 👨‍💻 Developer friendly
  Built in Python on Apify infrastructure — ideal for pipeline integrations, programmatic runs, and “Facebook comments scraper Python” workflows.

• 🔁 Automated workflows
  Combine with Apify integrations and schedulers to automate Facebook comment collection over time for social listening, campaign reporting, or moderation.

How to use Facebook Comments Scraper - step by step

1. Create or log in to your Apify account.
2. Open the “facebook-comments-scraper” actor in Apify Console.
3. Paste one or more public Facebook post or video URLs into startUrls (string list).
4. Configure limits:
   • maxComments: maximum comments to fetch per post.
   • maxRepliesPerComment: maximum replies fetched per top‑level comment (use a high number to get all).
   • commentsSortOrder: most_relevant, newest, or all.
     Note: proxyConfiguration is ignored — the actor automatically uses residential proxies.
5. Click Start to run. The actor will resolve IDs, page through comments, and attach replies where available.
6. Monitor logs to see progress (e.g., “Collected N comments so far…”).
7. When finished, go to the Output tab to view results and export Facebook comments to CSV or JSON.

Pro tip: Chain runs via the Apify platform to build an automated Facebook comments scraping tool that feeds dashboards, BI pipelines, or NLP sentiment analysis.

Use cases

Use case name	Description
Marketing analytics – campaign reporting	Measure engagement by extracting comment text, authors, timestamps, and reactions for post‑campaign analysis.
Social listening – brand monitoring	Track discussions at scale across public posts; scrape Facebook comments to power sentiment and topic modeling.
Community moderation – reply management	Export conversation threads to CSV/JSON, review at scale, and prioritize based on likesCount and commentsCount.
Competitive research – content benchmarking	Compare audience reactions across competitors’ public posts to identify content themes and messaging resonance.
Product research – feedback mining	Collect qualitative feedback from replies to feature announcements and launches to inform roadmaps.
Academic research – public discourse	Extract public comment threads for studies on engagement, discourse patterns, and information spread.
Data engineering – API pipelines	Use the structured output as a downstream source in ETL/ELT jobs and ML workflows for automated insights.

Why choose Facebook Comments Scraper?

This scraper is built for precision, automation, and reliability on public Facebook posts.

• 🎯 Accurate, structured results: Clean fields for text, author, timestamps, reactions, and replies.
• 🌍 Works on public posts: No Facebook login or cookies required; built for public data collection.
• 📈 Scales with your needs: Bulk input of multiple URLs to handle large monitoring or research jobs.
• 👩‍💻 Developer‑oriented: Python‑based actor on Apify — ideal for programmatic use and pipeline integration.
• 🔐 Safe & ethical by design: Targets publicly available content; you control limits and scope.
• 🔄 Production stability: Residential proxies and retries reduce blocking and transient failures.
• 💾 Easy export: Download Facebook comments to CSV/JSON for BI tools, spreadsheets, or databases.

Compared to fragile browser extensions or ad‑hoc scripts, this Facebook page comments scraper runs on managed infrastructure and returns analytics‑ready data consistently.

Is it legal / ethical to use Facebook Comments Scraper?

Yes — when used responsibly. This actor extracts comments from publicly available Facebook posts and videos only. It does not access private or authenticated content.

Guidelines for compliant use:

• Scrape only public data you are allowed to process.
• Review and respect Facebook’s Terms of Service.
• Ensure compliance with applicable data protection laws (e.g., GDPR, CCPA).
• Avoid collecting or using data in ways that could harm users’ privacy.
• Consult your legal team for edge cases or regulated workflows.

Input parameters & output format

Example JSON input

{
  "startUrls": [
    "https://www.facebook.com/humansofnewyork/posts/pfbid0BbKbkisExKGSKuhee9a7i86RwRuMKFC8NSkKStB7CsM3uXJuAAfZLrkcJMXxhH4Yl"
  ],
  "maxComments": 20,
  "maxRepliesPerComment": 2,
  "commentsSortOrder": "all",
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}

Input fields

Field	Type	Description	Default	Required
startUrls	array	Paste one or more Facebook post/video URLs to scrape comments from.	—	Yes
maxComments	integer	Maximum comments to fetch per post.	20	No
maxRepliesPerComment	integer	Max replies per comment (use a high number to fetch all).	2	No
commentsSortOrder	string (enum)	How to order comments: most_relevant, newest, or original order.	all	No
proxyConfiguration	object	Ignored. Actor always uses residential proxy automatically.	{ "useApifyProxy": false }	No

Note: The actor automatically uses residential proxies. Ensure your Apify plan includes Residential proxy access.

Example JSON output (successful comment item)

{
  "full_url": "https://www.facebook.com/SomePage/posts/1234567890",
  "url_key": "1234567890",
  "facebookUrl": "https://www.facebook.com/SomePage/posts/1234567890",
  "commentUrl": "https://www.facebook.com/.../comment/987654321",
  "id": "987654321",
  "feedbackId": "ZmVlZGJhY2sAbC1pZD0xMjM0NTY3ODk=",
  "date": "2026-03-28T06:09:00+00:00",
  "text": "Love this announcement!",
  "profilePicture": "https://scontent.xx.fbcdn.net/v/t1.0-1/...",
  "profileId": "1000123456789",
  "profileName": "Jane Doe",
  "likesCount": "7",
  "commentsCount": 1,
  "reply": [
    {
      "facebookUrl": "https://www.facebook.com/SomePage/posts/1234567890",
      "commentUrl": "https://www.facebook.com/.../comment/111222333",
      "id": "111222333",
      "feedbackId": "ZmVlZGJhY2sAbC1pZD0yMjIyMjIyMg==",
      "date": "2026-03-28T06:15:12+00:00",
      "text": "Thanks!",
      "profilePicture": null,
      "profileId": "1000987654321",
      "profileName": "John Smith",
      "likesCount": "1",
      "commentsCount": 0,
      "reply": [],
      "threadingDepth": 1,
      "facebookId": "1112223330",
      "inputUrl": "https://www.facebook.com/SomePage/posts/1234567890",
      "profileUrl": "https://www.facebook.com/john.smith"
    }
  ],
  "threadingDepth": 0,
  "facebookId": "9876543210",
  "inputUrl": "https://www.facebook.com/SomePage/posts/1234567890",
  "profileUrl": "https://www.facebook.com/jane.doe"
}

Example JSON output (error item for a post)

{
  "url_key": "1234567890",
  "full_url": "https://www.facebook.com/SomePage/posts/1234567890",
  "error": "Failed to extract doc_id or feedback_id",
  "comments": []
}

Notes:

• likesCount is returned as a string; commentsCount is an integer.
• Optional fields appear only when available: profilePicture, profileUrl, feedbackId, expansionToken, pageAdLibrary, threadingDepth.
• Items with no replies still include reply as an empty array.

FAQ

Is there a free trial?

✅ Yes. This actor includes trial minutes on Apify (120 minutes) so you can test scraping before subscribing. Usage beyond the trial follows the actor’s monthly pricing.

Do I need a Facebook login or cookies?

❌ No. The scraper targets publicly available posts and does not require a Facebook login or authenticated session.

Can I export results to CSV?

✅ Yes. After a run, open the dataset and export Facebook comments to CSV or JSON for your workflow.

Can it extract replies as well as comments?

✅ Yes. It collects top‑level comments and, where available, nested replies, returning a structured reply array for each comment.

How do I sort comments by relevance or recency?

🧭 Use the commentsSortOrder input with most_relevant, newest, or all to control ordering in the output.

How many comments and replies can I collect?

📈 Control depth with maxComments and maxRepliesPerComment. Set higher values to collect more; use practical limits for faster runs.

Does it work with Python or APIs?

💻 Yes. The actor runs on Apify and produces structured JSON datasets, ideal for “Facebook comments scraper Python” integrations or API‑driven pipelines.

What if my run shows proxy errors?

🛡️ The actor always uses residential proxies. Ensure your Apify plan includes Residential proxy access; otherwise, the run may fail at proxy setup.

Closing CTA / Final thoughts

Facebook Comments Scraper is built to reliably extract structured comments and replies from public Facebook posts at scale. It delivers clean fields for text, authors, timestamps, reactions, and threads — ready for sentiment analysis, social listening, and campaign reporting.

Whether you’re a marketer, developer, data analyst, or researcher, you can scrape Facebook comments across many URLs, sort by relevance or recency, and export to CSV/JSON for downstream use. Developers can automate runs and integrate outputs into pipelines with ease.

Start extracting smarter social insights today — run Facebook Comments Scraper and turn conversations into actionable data.