Facebook Comments Scraper

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Facebook Comments Scraper 🔍

Facebook Comments Scraper extracts comment threads from Facebook post URLs so you can collect, review, and analyze public discussion at scale. It helps teams that need a facebook comments scraper for scrape facebook comments workflows—whether you’re building datasets for facebook comments export, researching community sentiment, or powering downstream reporting. Whether you’re a marketer, data analyst, or researcher, this actor simplifies facebook post comments extractor tasks by turning public comment data into a structured dataset you can use immediately—saving you hours of manual work.

Why choose Facebook Comments Scraper?

Key features

• 🔎 Facebook post comments extraction: Scrapes comment threads from the Facebook post URLs you provide in startUrls.
• 🧾 Structured output for analysis: Produces fields like text, date, likesCount, commentsCount, and facebookUrl for each comment.
• 🗂️ Comments mode control: Choose Most relevant, Newest, or All to match how you want comments prioritized.
• 💬 Optional reply scraping: Enable includeReplies to also pull replies in your collected thread data.
• 🧠 Thread-aware parsing: Captures comment URLs/IDs and author metadata (e.g., profileName, profileId, profilePicture) alongside the comment text.
• 🛡️ Retry and resilience handling: Uses retries with exponential backoff during requests to improve completion reliability.
• 💾 Dataset-ready saving: Pushes results to an Apify dataset continuously during pagination.
• 🌐 URL list input: Accepts a list of Facebook URLs so you can run bulk facebook comments scraper workflows.

Input

Provide input via an input.json file. Example structure:

{
"startUrls":[
{
"url":"https://www.facebook.com/humansofnewyork/posts/pfbid0BbKbkisExKGSKuhee9a7i86RwRuMKFC8NSkKStB7CsM3uXJuAAfZLrkcJMXxhH4Yl"
}
],
"resultsAmount":50,
"includeReplies":false,
"commentsMode":"All"
}

Input Fields

Output

The actor saves each collected comment record to the default Apify dataset as structured JSON objects.

[
{
"facebookUrl":"https://www.facebook.com/example",
"commentUrl":"https://www.facebook.com/some/path?comment_id=123",
"commentId":"123",
"id":"4567890",
"feedbackId":null,
"date":"2024-01-01T00:00:00.000Z",
"text":"This is the comment text",
"profilePicture":"https://example.com/avatar.jpg",
"profileId":"111222333",
"profileName":"Author Name",
"likesCount":"12",
"commentsCount":3,
"comments":[],
"threadingDepth":0,
"pageAdLibrary":{
"is_business_page_active":false,
"id":"999999999"
},
"facebookId":"987654321",
"postTitle":"Optional post title if available",
"inputUrl":"https://www.facebook.com/example"
}
]

Output Fields

Export formats: results are stored in an Apify dataset and can be exported from the Apify Console (e.g., JSON and CSV depending on your workflow).

How to use Facebook Comments Scraper (via Apify Console)

1. Open Apify Console
   Log in at console.apify.com and go to the Actors tab.

2. Find Facebook Comments Scraper
   Search for Facebook Comments Scraper and open the actor details page.

3. Go to the INPUT section
   Use the built-in input form to add your Facebook post URLs in startUrls.

4. Set your limits and behavior
   Configure resultsAmount (max comments per URL), decide whether includeReplies should be enabled, and choose commentsMode (Most relevant, Newest, or All).

5. (Optional) Adjust proxy settings
   If you’re running into access issues, you can set proxy configuration in the run input. This actor includes built-in proxy support and resilience features for more reliable scraping.

6. Click Run
   Start the actor run and monitor logs. You should see progress as it fetches and paginates through comment data.

7. Open the OUTPUT dataset
   After completion, check the Results dataset where each comment record is saved.

8. Export your data
   Export the dataset for reporting, analysis, or a facebook comments export pipeline (commonly to JSON/CSV depending on your needs).

No coding required—get accurate results in minutes with this facebook comments scraper.

Advanced features & SEO optimization

• 🔧 Engineered for Facebook comments analysis scraper workflows: Designed to collect key engagement signals like likesCount and commentsCount alongside the comment text for easier downstream analysis of public discussion.
• 🎛️ Precise control with comments mode: Use commentsMode to switch between Most relevant, Newest, and All comment ranking.
• 📌 Bulk-ready dataset building: Feed multiple URLs through startUrls to power facebook comments collection tool use cases and bulk facebook comments scraper runs.
• 🔄 Resilient pagination & retries: Includes retries and fallbacks to improve completion success across different targets.
• 💾 Structured output schema: Consistent fields like profileName, date, facebookUrl, and commentUrl make results easy to import into your pipelines.

Best use cases

• 📈 Marketing teams building community insights: Extract public discussion from multiple posts and assemble a clean dataset for sentiment or topic analysis.
• 🧑‍🔬 Researchers analyzing engagement patterns: Compare likesCount and reply volume (commentsCount) across posts and time.
• 🗞️ Content strategists validating audience response: Quickly review comment text and metadata after launching content, then export for reporting.
• 🧑‍💼 Community managers monitoring feedback: Collect comments (and optionally replies) into a single place for review and moderation workflows.
• 🧱 Data analysts preparing structured datasets: Use the consistent output fields to join comment data with other sources in a data warehouse.
• 💻 Developers automating export pipelines: Integrate dataset outputs into scheduled workflows for a facebook comment downloader style automation.
• 🧠 Lead research & outreach preparation: When you use publicly available data ethically, you can aggregate commenter profiles to inform outreach research (always follow relevant policies and laws).

Technical specifications

Supported Input Formats

• ✅ startUrls: List of Facebook post URLs (as objects with url, or plain URL strings depending on your input).
• ✅ resultsAmount (integer): Maximum comments per URL (default 50).
• ✅ includeReplies (boolean): Whether replies are included (default false).
• ✅ commentsMode (string): Most relevant, Newest, or All (default All).

Proxy Support

• ✅ Built-in proxy support for more reliable scraping runs.
• ❗ Proxy configuration can be provided via input (the actor uses proxy settings when available).

Retry Mechanism

• ✅ Retries are used during requests with exponential backoff to improve robustness.

Dataset Structure

• ✅ Default dataset view titled Results with columns for: profileName, text, date, likesCount, commentsCount, and facebookUrl.

Rate Limits & Performance

• ⚠️ Performance varies based on target availability and access conditions.
• ✅ The actor respects resultsAmount as a cap per URL during pagination.

Limitations

• ❌ Private/restricted content is not guaranteed to be accessible.
• ❌ Some fields (e.g. commentUrl, commentId, or postTitle) may be null when not available in the extracted data.

FAQ

What does the Facebook Comments Scraper actually scrape?

✅ It scrapes public comment data from the Facebook post URLs you provide in startUrls, returning fields such as comment text, date, likesCount, and author information like profileName and profileId.

Can I scrape replies, not just top-level comments?

✅ Yes. Enable includeReplies to also scrape replies to comments (default is false).

How do commentsMode options affect the results?

✅ commentsMode controls the ranking behavior for comments using one of these values: Most relevant, Newest, or All (default: All).

How many comments do I get per URL?

✅ The actor uses resultsAmount as the maximum number of comments to scrape per URL (default: 50).

Where do the results go?

✅ Results are saved to the actor’s default Apify dataset under the Results view, with table columns like profileName, text, date, likesCount, commentsCount, and facebookUrl.

Is there a way to use this in an automated workflow?

✅ Yes. You can run the actor with input JSON and then export the dataset output to your downstream systems as part of a pipeline—perfect for a facebook comments collection tool or facebook comments export process.

Do I need coding to use it?

✅ No. You can use Apify Console’s INPUT form to provide startUrls, configure resultsAmount, includeReplies, and commentsMode, then export your dataset.

Is it legal to scrape public Facebook comments?

✅ The actor accesses publicly available sources only, but whether scraping is permitted depends on applicable laws and platform policies. You’re responsible for compliance (including GDPR/CCPA where relevant) and for using the data ethically.

Support & feature requests

Have questions or want to improve this Facebook Comments Scraper? We’d love your feedback. 💬

• 💡 Feature Requests: Examples include exporting directly to CSV, adding more comment/thread fields, or supporting additional output formats for facebook comments analysis scraper workflows.
• 📧 Contact: Send support requests to dataforleads@gmail.com.

User feedback directly shapes the roadmap for this facebook comments scraper.

Closing CTA / Final thoughts

If you need the most comprehensive and SEO-optimized way to scrape and export Facebook comment data, Facebook Comments Scraper is built for exactly that.
Run it against your post URLs, set your resultsAmount, and start building your facebook comments export dataset today.

Disclaimer

This tool only accesses publicly accessible sources. It does not access private profiles, authenticated data, or password-protected pages.

You are responsible for ensuring your use complies with applicable laws and regulations (including GDPR/CCPA where relevant), spam and privacy rules, and the platform’s Terms of Service. For data removal requests, contact dataforleads@gmail.com.

Please use this actor responsibly, ethically, and for legitimate purposes only.