YouTube Comments Scraper

Overview

This actor automatically extracts comments and metadata from YouTube videos. It bypasses the limitations of the official API, providing richer data like author details, replies, likes, and timestamps. It's designed for automation, lead generation, and social media analysis.

Key Features

• Data Extraction: Collects comment text, author name, channel info, timestamp, likes, reply count, and pinned/hearted status.
• Sorting: Choose between Top Comments (most liked/relevant) or Newest First.
• Bulk Processing: Scrape comments from multiple video URLs or entire playlists in a single run.
• Export Formats: Download results as CSV, Excel, JSON, or XML for easy integration.
• Scalability: Handles projects ranging from a single video to hundreds of links.
• Integration: Connect scraped data to AI/NLP models for sentiment analysis, trend detection, or keyword clustering.

How to Use

1. Log in to your Apify account.
2. Select the Actor from the Apify Store.
3. Enter Input: Paste one or more YouTube video URLs into the Start URLs field. You can also upload a CSV or Google Sheet containing links.
4. Configure Options: Set the sort order, maximum number of comments, and choose whether to include replies or detect pinned/hearted comments.
5. Run: Click Start. The scraper will collect comments and display progress in the console.
6. Download Results: Export your dataset in your preferred format (JSON, CSV, Excel, XML) or send it directly to tools like Google Sheets, Make, Zapier, or Slack.

Input/Output

Input Configuration (example):

{
  "startUrls": ["https://www.youtube.com/watch?v=VIDEO_ID"],
  "sortOrder": "top", // or "newest"
  "maxComments": 1000,
  "includeReplies": true
}

Output Data:
The actor outputs a structured dataset. Each item typically includes:
* text: The full comment text.
* author: Commenter's display name and channel ID.
* timestamp: When the comment was posted.
* likes: Number of likes on the comment.
* replyCount: Number of replies.
* isPinned / isHearted: Boolean flags for creator interactions.

Results are ready for direct analysis in spreadsheets, BI tools, or custom data pipelines.