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Home/How-To Guides/How to Scrape YouTube Comments
YouTube

How to Scrape YouTube Comments

Extract comments data from YouTube at scale

Step-by-step guide

1

Choose your YouTube comments scraper

Navigate to the YouTube Comments scraper and select "Fresh Scrape" for real-time data or "Quick Lookup" for pre-collected records. Each record costs 1 credit.

2

Provide your YouTube input URLs

Paste the YouTube URLs you want to scrape — one per line, or upload a CSV. Scrapernode accepts direct profile links, search result URLs, and hashtag pages.

3

Launch your scraping job

Click "Start Extraction" to begin. Scrapernode handles proxy rotation, rate limiting, and anti-bot detection automatically. Jobs typically complete in under 60 seconds per batch.

4

Download structured data

Once complete, download your results as JSON or CSV. Each record includes 15 structured fields like comment_id, comment_text, likes, replies, and more.

5

Automate with webhooks or API

Set up webhooks to receive data automatically when jobs complete, or use the REST API for programmatic scraping. Integrate with n8n, Make, or Zapier for workflow automation.

Cost per record

1 credit

Output fields

15 fields

Output formats

JSON, CSV

Sample Output

Preview the data you'll receive — 5 sample records

Record 1 of 5
Comment Id
sample_comment_id
Comment Text
Great analysis! Would love to see a deeper dive on the retention metrics.
Likes
34,108
Replies
37
Username
@sarahchen
Username Md5
sample_username_md5
User Channel
sample_user_channel
Date
2025-12-15
Url
sample_url
Video Id
sample_video_id
Replies Value
sample_replies_value
Replies Without Names
sample_replies_without_names
User Id
sample_user_id
Mentioned Timestamps Minutes
sample_mentioned_timestamps_minutes
Mentioned Timestamps Seconds
sample_mentioned_timestamps_seconds

Data Dictionary

15 fields returned per record

Unique identifier for each comment (100.00% fill rate)

The text content of the comment (99.98% fill rate)

Number of likes received by the comment (100.00% fill rate)

Number of replies to the comment (99.97% fill rate)

Username of the commenter (99.95% fill rate)

MD5 hash of the username field (99.97% fill rate)

URL of the commenter's YouTube channel (100.00% fill rate)

Date when the comment was posted (100.00% fill rate)

Web address of the YouTube video where the comment was posted (100.00% fill rate)

Unique identifier for the YouTube video (97.47% fill rate)

Reply values (3.00% fill rate)

Sub-fields

authorTextReply author name
textTextReply text
dateTextReply date
likesNumberReply likes count

Replies without names (3.00% fill rate)

Sub-fields

textTextReply text without author name
dateTextReply date
likesNumberReply likes count

User ID of the commenter (97.19% fill rate)

Timestamps mentioned in the comment (minutes) (0.08% fill rate)

Timestamps mentioned in the comment (seconds) (0.08% fill rate)

Frequently Asked Questions

Common questions about How to Scrape YouTube Comments

Ready to scrape YouTube?

Start extracting youtube comments data in minutes. No code required — just paste your URLs and go.

Go to YouTube Comments scraperBrowse all guides
No code requiredJSON & CSV exportAPI & webhook support