5 Best Facebook Comments Scraper Tools in 2026

Facebook comments can reveal customer complaints, product questions, campaign reactions, community concerns, and recurring audience interests. Collecting this information manually becomes inefficient when a project involves several posts, videos, Reels, or long reply threads.

A Facebook Comments Scraper converts publicly accessible discussions into structured records. The best tool depends on whether the team needs a simple spreadsheet, nested conversation data, recurring monitoring, or an API connected to an analytics system.

Best Facebook Comments Scraper Tools Compared

What Is a Facebook Comments Scraper?

A Facebook Comments Scraper is a tool that collects publicly accessible comments from Facebook posts and converts them into structured data. Instead of manually copying comment text, replies, timestamps, reactions, and commenter information, users can process selected post URLs and organize the results for further analysis.

Depending on the tool and the available public content, a Facebook Comments Scraper may collect comment IDs, text, reply relationships, like counts, publication dates, profile names, post IDs, and source URLs. The data can support sentiment analysis, audience research, campaign reporting, community monitoring, and content moderation.

The 5 Best Facebook Comments Scraper Tools

1. CoreClaw

The CoreClaw Facebook Comments Scraper accepts one or more public Facebook post URLs and returns structured comment content, commenter information, likes, reactions, timestamps, reply counts, comment IDs, links, and nested replies. It supports CSV and JSON export without requiring users to build or maintain scraping infrastructure.

Users can set a maximum result count, choose how comments are sorted, and enable nested comments. The current input schema supports up to three reply levels, making the Worker useful for both flat sentiment datasets and basic conversation analysis.

Best for: Marketing teams, agencies, researchers, and non-technical users.

Advantages:

• Batch post URLs
• No-code operation
• Structured and normalized output
• Nested reply collection
• CSV and JSON export
• API and scheduled workflows
• Failed results do not count as successful results

The current Worker page lists pricing from $1.70 per 1,000 successful results on the Business tier, with higher unit rates on lower plans. Pricing should be confirmed before each project.

2. Apify

Apify’s maintained Facebook Comments Scraper processes posts, images, videos, and Reels. It can collect comment text, URLs, timestamps, likes, commenter details, replies, Facebook IDs, and threading depth.

The Actor supports comment sorting, date filtering, API runs, webhooks, Python and Node.js clients, and exports to JSON, CSV, Excel, or HTML.

Best for: Developers and growth teams that need configurable automation.

Advantages:

• Maintained directly by Apify
• Extensive comment and reply fields
• Scheduling and webhook support
• Broad integration ecosystem
• Multiple export formats

Limitation: Apify uses residential proxy infrastructure for stable Facebook collection, and larger workflows may require closer platform-usage and cost monitoring. Its current listed price starts from $1.40 per 1,000 comments.

3. Bright Data

Bright Data offers dedicated Facebook scraper endpoints covering comments, posts, Pages, profiles, groups, Reels, events, and other public data types. Its Facebook Comments Scraper can return comment URLs, post identifiers, commenter details, creation dates, likes, replies, and other structured fields.

Bright Data manages proxy routing, access infrastructure, parsing, and large API jobs.

Best for: Enterprise data teams and recurring social-listening systems.

Advantages:

• Dedicated Facebook endpoints
• Structured API output
• Managed access infrastructure
• Suitable for large batch pipelines
• Broader Facebook data coverage

Limitation: The API-first setup is more technical than most one-time Excel projects require.

4. ExportComments

ExportComments is designed for users who want a downloadable file rather than a complete scraping platform. It supports public Facebook posts, Page videos, Reels, public group posts, and public profile posts.

Each comment becomes a structured Excel, CSV, or JSON row containing the author, comment text, timestamp, reactions, parent-comment connection, permalink, and attachment details. Replies can remain linked to their parent comments.

Best for: Social media managers, agencies, giveaway organizers, and spreadsheet-first analysts.

Advantages:

• Simple URL-based workflow
• Excel, CSV, and JSON delivery
• Replies and reaction breakdowns
• Public Page, group, profile, video, and Reel support
• Free tier for small tests

Limitation: It is less suitable for teams that need custom extraction logic or broader web-data infrastructure.

5. ScrapeCreators

ScrapeCreators provides an unofficial REST API with dedicated endpoints for Facebook post comments and comment replies. Results are returned as JSON and can feed applications, dashboards, sentiment-analysis pipelines, or automated reporting systems.

The service also provides endpoints for public profiles, posts, Reels, photos, groups, and related Facebook data.

Best for: Developers that want straightforward comments and replies endpoints.

Advantages:

• Focused REST endpoints
• Separate comment-reply endpoint
• Real-time JSON responses
• Simple API-key authentication
• Free credits for initial testing

Limitation: It is an unofficial API, so teams must independently evaluate reliability, platform-policy exposure, and long-term vendor risk.

How to Prepare Facebook Comments for Analysis

Do not treat the first export as a finished dataset.

Remove duplicates using comment IDs. Keep replies connected to parent comments, and separate post-author replies from audience comments. Standardize timestamps, reaction fields, URLs, and language labels.

For sentiment analysis, create separate columns for:

• Overall sentiment
• Discussed topic
• Topic-level sentiment
• Question or complaint type
• Reply status
• Manual-review status

Emoji-only comments, sarcasm, copied giveaway entries, spam, and multilingual discussions may require additional rules or human review.

Additional public Facebook data tools are available in the CoreClaw Facebook Scraper Store. Recurring projects can use the CoreClaw API integration workflow to start Workers, monitor runs, retrieve results, and send cleaner datasets into dashboards or internal systems.

Is It Safe to Scrape Facebook Comments?

Meta’s Automated Data Collection Terms define automated collection broadly and require express written permission or another form of explicit authorization for automated collection from Meta products. Teams should review those terms, Meta’s technical instructions, provider policies, privacy laws, and their intended use before starting a project.

Collect only necessary public information. Avoid private groups, friends-only posts, restricted content, sensitive profiling, harassment, or unrelated individual targeting.

For comments on Pages managed by the organization, Meta’s official Graph API may be the more appropriate route. Access to certain Page-post comment fields requires the relevant Page permissions or management tasks.

Final Thoughts

The best Facebook Comments Scraper depends on the required output and operating model.

Bright Data is suited to enterprise pipelines, Apify provides flexible automation, ExportComments focuses on spreadsheets, and ScrapeCreators offers a compact developer API.

For most agencies, researchers, and business teams, CoreClaw provides the most balanced workflow. Teams can process public post URLs without coding, collect comments and nested replies as structured data, export CSV or JSON files, and connect recurring tasks through an API.

CoreClaw also provides ready-made Workers for Facebook posts, profiles, events, and other public social-data workflows. Developers can build specialized Workers in Python, Node.js, or Go when a project requires custom filtering, classification, or downstream automation.