Use Youtube Comment Scraper for Free
What is Youtube Comment Scraper ?
DICloak YouTube Comment Scraper is a tool that automatically extracts comments from YouTube videos, including usernames, timestamps, likes, replies, and the comment content itself. It’s useful for sentiment analysis, audience research, trend tracking, and content optimization. The scraper collects large volumes of comment data efficiently, outputting results in structured formats like CSV or JSON. However, scraping YouTube can violate Google’s Terms of Service, and techniques such as CAPTCHA solving are often necessary to avoid detection.
What Makes Youtube Comment Scraper Special?
DICloak YouTube Comment Scraper stands out due to the following features:
Bypass Anti-Scraping Measures
DICloak allows users to configure dynamic proxies for IP rotation. With high-quality proxy IPs and customized browser fingerprint settings, it can help bypass YouTube’s anti-scraping mechanisms, such as rate-limiting, CAPTCHA, and request throttling—ensuring more stable, long-term scraping operations.
Scalability
DICloak’s scalable architecture allows users to handle bulk comment scraping across multiple videos or channels, adapting to different workloads without sacrificing speed or reliability.
Cloud Integration
The scraper can be deployed on cloud platforms for remote operation, automation, and scheduling, giving users convenient access to manage scraping tasks and retrieve data from anywhere.
Real-Time Data Collection
DICloak supports near real-time comment extraction, capturing new comments as they are posted. This is especially valuable for tracking engagement trends or monitoring video feedback during critical time windows.
Comprehensive Data Extraction
It extracts detailed metadata such as commenter usernames, timestamps, number of likes, comment threads (replies), and comment text—providing rich insights into audience sentiment and engagement.
Conclusion
These features make DICloak YouTube Comment Scraper a powerful tool for content creators, marketers, researchers, and analysts aiming to collect and study YouTube engagement data accurately, efficiently, and securely.
Why Choose Dicloak Youtube Comment Scrapers?
Enhanced Anonymity
DICloak uses advanced fingerprint randomization and session control to ensure scraping sessions stay undetected, helping prevent YouTube from flagging or throttling your IP.
Avoid Detection and Blocks
DICloak allows users to configure dynamic proxies for IP rotation. With proxy rotation and user-agent switching, DICloak allows you to scrape YouTube comments safely, minimizing the risk of request blocks and detection—even during high-volume tasks.
Efficient Data Collection
DICloak supports high-speed scraping and efficiently handles large-scale extraction of comments across multiple videos or channels, making it ideal for collecting engagement data in bulk.
Customization
With flexible filters and keyword targeting, DICloak lets you customize scraping by video ID, comment type (top/recent), and even reply depth—optimizing the process for your specific research or analysis goals.
Security
DICloak ensures secure comment data extraction by using encrypted requests and session isolation, providing peace of mind for users concerned with privacy and data integrity.
Other Youtube Comment Scrapers That Meet Your Needs
YouTube Video Comment Extractor
Extract all comment details from any YouTube video, including usernames, comment text, likes, timestamps, and pinned status. Just input the video URL, and DICloak will collect engagement data that’s useful for content analysis, sentiment tracking, or audience research.
Channel-Wide Comment Scraper
Target entire YouTube channels to extract comments from all public videos. This helps when analyzing long-term engagement trends, monitoring influencer channels, or collecting training data for machine learning.
Comment Thread (Replies) Scraper
Capture complete comment threads, including top-level comments and all nested replies. Useful for analyzing discussions, sentiment shifts, and community interactions within a video’s comment section.
Need Deeper Insights?
If basic comment data isn’t enough, DICloak also allows metadata enrichment—like extracting comment translation options, badge roles (e.g., creator, moderator), and video interaction metrics. This expanded view gives you a fuller picture of user engagement on YouTube.
FAQs
What are the differences between Youtube Comment API and DICloak Youtube Comment Scrapers?
The YouTube Data API is an official, compliant service offered by Google that provides structured access to limited comment data. It requires an API key and operates under quota restrictions—allowing only a certain number of comments per request and per day. DICloak YouTube Comment Scraper bypasses these limitations by directly scraping the YouTube interface. It provides full comment threads, like counts, pinned status, and user metadata without needing API keys or being bound by rate limits. However, it may involve more complex setup and should be used responsibly in line with platform terms.
What’s so special about Youtube Comment Scraper?
The DICloak YouTube Comment Scraper is unique for its ability to extract large volumes of comment data without relying on official APIs or quotas. It captures full metadata—including usernames, timestamps, likes, replies, and pinned comments—and supports the collection of nested comment threads. With no pagination limits and full control over how and what data is collected, it’s a powerful tool for sentiment analysis, research, and engagement monitoring.
Can I customize a Youtube Comment Scraper?
Yes, DICloak allows you to fully customize your scraping tasks based on your needs. You can filter by keyword or date range, sort by top or newest comments, control reply depth, and define output formats such as JSON or CSV. Proxy integration, error handling, and scheduling tools ensure your setup remains efficient and undetected, even during long scraping sessions.
Can I run the scraping task in the cloud?
Definitely. DICloak YouTube Comment Scraper supports cloud deployment through platforms like AWS, Google Cloud, and Azure. You can run scraping tasks in virtual machines or containers, automate them with cron jobs or AWS CloudWatch, and store output in cloud storage like S3 or Google Drive. This makes it ideal for large-scale, recurring tasks that require speed, reliability, and scalability.