💬 Facebook Comments Scraper

Extract comments from any public Facebook post, reel, or video at scale. Collect comment text, author details, timestamps, like counts, and reply metadata — ready for export as JSON, CSV, or Excel.

🔍 What does Facebook Comments Scraper do?

This scraper collects all publicly visible comments from Facebook posts. Just paste one or more post URLs and the scraper returns structured data for every comment, including replies.

Use it for 📊 brand monitoring, 🧠 sentiment analysis, 🕵️ competitor research, 👂 social listening, 📝 content analysis, 📸 UGC collection, and 📈 market research.

📦 What data can you extract?

For every comment, the scraper returns:

Field	Description
text	💬 Full comment text
authorName	👤 Commenter's display name
authorId	🆔 Commenter's Facebook user ID
commentId	🔖 Unique comment ID
likesCount	👍 Number of likes/reactions on the comment
timestamp	🕐 Unix timestamp (milliseconds) when the comment was posted
isReply	↩️ Whether this is a reply to another comment
postUrl	🔗 URL of the parent post

🚀 How to scrape Facebook comments

1. 🔗 Go to the Facebook post you want to scrape comments from
2. 📋 Copy the post URL from your browser's address bar
3. 📝 Paste the URL(s) into the scraper input
4. 🔢 Set the limit — how many comments per post (default: 500)
5. ▶️ Run the scraper and download your data

🌐 Supported URL formats

• 📄 Page posts: https://www.facebook.com/PageName/posts/123456789
• 🎬 Video posts: https://www.facebook.com/PageName/videos/123456789
• 🎞️ Reel posts: https://www.facebook.com/reel/123456789
• 🔗 Permalink format: https://www.facebook.com/permalink.php?story_fbid=...
• 🔗 Short links: https://fb.watch/...

⚙️ Input parameters

Parameter	Type	Description
postUrls	Array of strings	🔗 List of Facebook post URLs to scrape comments from
maxCommentsPerPost	Integer	🔢 Maximum comments to collect per post (default: 500, max: 50,000)
viewOption	String	🔀 Comment sort order: RANKED_UNFILTERED (All), RANKED_THREADED (Most relevant), RECENT_ACTIVITY (Newest first)
includeReplies	Boolean	💬 Include reply comments nested under top-level comments (default: true)

📥 Example input

{
    "postUrls": [
        "https://www.facebook.com/Meta/posts/1075637535125456",
        "https://www.facebook.com/cnn/posts/1194948395660316"
    ],
    "maxCommentsPerPost": 1000
}

📤 Example output

{
    "postUrl": "https://www.facebook.com/Meta/posts/1075637535125456",
    "text": "This is amazing! Love the community spirit 🎳",
    "authorName": "John Smith",
    "authorId": "100012345678",
    "likesCount": 42,
    "timestamp": 1783701511000
}

💰 How much does it cost to scrape Facebook comments?

The scraper uses Apify's pay-per-result pricing. You only pay for the comments you actually get.

• 🆓 Free tier: 10 comments per run — test before you buy, no credit card needed
• ⚡ Performance: ~600 comments per minute
• 🪶 Memory: Runs on just 128 MB — minimal compute cost

Check the Pricing tab above for current per-result rates.

💡 Use cases

📊 Brand monitoring & reputation management

Track what customers say about your brand, products, or services across Facebook. Collect comments from your brand's posts or competitor pages to measure sentiment and spot issues early.

🧠 Sentiment analysis & NLP

Feed structured comment data into your sentiment analysis pipeline. Each comment includes text, timestamp, and engagement metrics — perfect for time-series sentiment tracking.

🕵️ Competitor research

Analyze how audiences respond to competitor content. Compare engagement patterns, identify common complaints, and discover what resonates with their audience.

📸 Content research & UGC

Find user-generated content, testimonials, and authentic customer feedback. Identify brand advocates and understand what drives engagement.

👂 Social listening at scale

Monitor comments across dozens of posts simultaneously. Set up recurring runs to track conversations over time.

🎓 Academic & market research

Collect public Facebook comment data for research purposes. Export as CSV or JSON for analysis in Python, R, SPSS, or Excel.

🔌 Integrations

Connect Facebook Comments Scraper to your workflow:

• 📊 Google Sheets — auto-export comments to a spreadsheet
• 💬 Slack / Discord — get notified when scraping completes
• ⚡ Zapier / Make — trigger downstream workflows
• 🪝 Webhooks — POST results to your own API
• ☁️ Amazon S3 / Google Cloud — store datasets in cloud storage

Use the Apify API or any of the official Apify client libraries (JavaScript, Python) to integrate programmatically.

🤖 MCP server integration (AI agents & LLMs)

This actor works as a tool for AI agents via the Apify MCP server. Connect it to Claude, ChatGPT, Cursor, Windsurf, or any MCP-compatible AI assistant to let your agent scrape Facebook comments on demand.

🟣 Use with Claude Desktop / Claude Code

Add the Apify MCP server to your Claude config:

{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": ["-y", "@anthropic-ai/apify-mcp-server"],
            "env": {
                "APIFY_API_TOKEN": "YOUR_APIFY_TOKEN"
            }
        }
    }
}

Then ask Claude: "Scrape comments from this Facebook post: https://www.facebook.com/Meta/posts/1075637535125456"

🟢 Use with OpenAI / GPT agents

Apify actors are available as OpenAI tools via the Apify platform. See Apify + OpenAI integration docs.

🦜 Use with LangChain / LlamaIndex

from langchain_community.utilities import ApifyWrapper

apify = ApifyWrapper()
loader = apify.call_actor(
    actor_id="YOUR_ACTOR_ID",
    run_input={"postUrls": ["https://www.facebook.com/Meta/posts/1075637535125456"]},
    dataset_mapping_function=lambda item: item["text"],
)

🧩 Why use this with AI agents?

• 🔬 Research automation: Let your agent collect and analyze Facebook discussions autonomously
• 📚 RAG pipelines: Feed real-time Facebook comment data into retrieval-augmented generation
• 📊 Sentiment workflows: Agent scrapes comments → analyzes sentiment → generates report
• 🕵️ Competitive intel: Agent monitors competitor Facebook pages and summarizes audience reactions

🔧 API access

Call the scraper from your code using the Apify API:

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")
run = client.actor("YOUR_ACTOR_ID").call(run_input={
    "postUrls": ["https://www.facebook.com/Meta/posts/1075637535125456"],
    "maxCommentsPerPost": 500,
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["authorName"], item["text"][:80])

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_API_TOKEN' });
const run = await client.actor('YOUR_ACTOR_ID').call({
    postUrls: ['https://www.facebook.com/Meta/posts/1075637535125456'],
    maxCommentsPerPost: 500,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach(item => console.log(item.authorName, item.text));

❓ FAQ

🔐 Does this scraper need my Facebook login?

No. The scraper works without your Facebook credentials.

🔢 How many comments can I scrape?

Up to 50,000 comments per post. Most posts have fewer than 10,000 comments.

🔒 Can I scrape comments from private posts or groups?

No. Only publicly visible comments are accessible.

⚡ How fast is it?

~600 comments per minute on average. A post with 1,000 comments takes about 2 minutes.

💬 Does it include replies to comments?

Yes. The "All comments" mode captures top-level comments and all replies.

📱 What Facebook post types are supported?

Regular posts, photos, videos, reels, live videos, and shared posts from public pages and profiles.

🔍 Can I filter comments by date or keyword?

The scraper collects all comments with timestamps. Use the exported data to filter by date, keyword, or any other field in your analysis tool.

⚖️ Is scraping Facebook comments legal?

This scraper only accesses publicly visible data. Always review Facebook's Terms of Service and applicable data protection regulations (GDPR, CCPA) before using scraped data.