📘 Facebook Comments Scraper

🚀 Overview

Facebook Comments Scraper is a lightweight but powerful Apify actor that pulls high-signal discussion data from public Facebook posts.

It extracts every top-level comment — along with detailed engagement metrics like 👍 likes, 💬 replies, and ⏱ timestamps — allowing you to convert unstructured social conversations into actionable insights.

Whether you're a marketer, researcher, developer, or data analyst, this tool helps you stay ahead by providing real-time visibility into audience reactions, emerging trends, and content performance.

It’s especially useful for:

• 🧠 Product & Brand Sentiment Analysis: Understand how users are reacting to your products, ads, or brand mentions in public Facebook posts.
• 📣 Influencer Campaign Monitoring: Track how well influencer posts are engaging audiences across different regions or demographics.
• 📊 Market Research: Spot behavioral patterns and collect qualitative data for targeted surveys or segmentation.
• 🏛 Political & Social Research: Scrape comment sections on political or policy-related posts to monitor public opinion and voter sentiment.
• 🚨 Misinformation & Content Moderation Studies: Detect engagement patterns around false claims or toxic discussions.
• 🎓 Academic Studies: Use as a dataset generator for NLP models, opinion mining, or social media discourse analysis.

This actor enables automated, scalable, and repeatable comment extraction — no browser automation, no manual effort.

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🛠 Key Features

🔹 Feature	💡 What you get
📝 Comment body	Full text, emoji and all.
🙋 Author info	Commenter ID and profile link (when public).
🕒 Timestamps	Exact UNIX time to analyse activity peaks.
📈 Engagement	• likes_count (integer) 👍 • reply_count (integer) 💬 • is_live_video_comment flag
📦 Multiple formats	JSON, CSV, Excel, XML or HTML via Apify storage.

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⚡ Quick Start

1. 🔁 Clone / fork the actor or install from Apify Store
2. 🌐 Put your post URLs in storage/key_value_stores/default/INPUT.json
3. ▶️ Click “Save & Start”

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🧾 Input Parameters

{
    "maxResults": 40,
    "startUrls": ["https://www.facebook.com/Cristiano/posts/10161345601032164"]
}

📤 Output Example

Each output item includes:

"comment_id": "17938403948273912",
    "feedback_id": "1837320198273947",
    "commentor_id": "1000123456789",
    "comment_text": "This goal was insane 🔥",
    "author": {
        "name": "John Doe",
        "url": "https://facebook.com/johndoe"
    },
    "created_time": 1719814023,
    "is_live_video_comment": false,
    "likes_count": 235,
    "reply_count": 12
}

• 📁 Data is stored in Apify's dataset — export it as JSON, CSV, Excel, or HTML.

💬 Feedback & Support

We appreciate your support and contributions! 🤝

🐛 Found a bug? 💡 Want a feature added?

1. Open an Issue in the GitHub issues tab.
2. Include the run ID or error message, if available.
3. We aim to respond within 24 hours ⏳