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Analyze Top Xiaohongshu Comment Threads

Collect the most-liked Xiaohongshu comments and their replies. Export complete discussion threads with authors, engagement, timestamps, and structured data.

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Xiaohongshu Comments Scraper - Reply Threads (RedNote)
Xiaohongshu Comments Scraper - Reply Threads (RedNote)zen-studio/rednote-comments-scraper
Comment ID
Comment
Author
Likes
+30 fields
Text
Number
Boolean
List
Object

Input

🔗 Note URLs, share links, or IDs(required):https://www.xiaohongshu.com/discovery/item/69db721a00000000220290a8
Sort comments by:most_liked
Include replies under each comment:true
Max comments per note:100
Max replies per comment:10

Output fields

Comment ID
Comment
Author
Likes
Reply count
IP location
Posted (Unix)
Replies (nested)
Attached pictures
@-mentions
Tags (v2)
Tags
Hashtags
Note ID
Note URL
Liked
Media source type
Index in note
Sort
Status
Hidden
Downvoted
Collected
Relatable to note
Score
Share strategy
Comment type
Translation strategy
Show type
Business label
Track ID
Friend-liked message
Sub-comments (raw inline)
Sub-comment cursor

How it works

Sign up on Apify or log in

The Xiaohongshu Comments Scraper - Reply Threads (RedNote) Actor is ready to run with the inputs already set for "Analyze Top Xiaohongshu Comment Threads". Sign up or log in and you'll land in Apify Console with a copy of this exact task.

Start the "Analyze Top Xiaohongshu Comment Threads" task

The Xiaohongshu Comments Scraper - Reply Threads (RedNote) Actor will start running based on the input automatically. You can also change all the input fields, like 🔗 note urls, share links, or ids, sort comments by, and more, to match your specific use case.

Receive the "Analyze Top Xiaohongshu Comment Threads" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as comment id, comment, author, and more.

Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also run the "Analyze Top Xiaohongshu Comment Threads" task via API.

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