Xiaohongshu (RED) Explore Scraper — engagement by channel

Fetch Xiaohongshu explore feeds channel by channel and get notes with like counts, plus a breakdown that tells you how each channel actually behaves.

Most Xiaohongshu scrapers hand you a flat list of notes. The useful question is which channel rewards what — and that only shows up when you compare channels side by side.

What you get per note

Field	Example
channel	fitness
title	the note's display title
likes	31000
isVideo, noteType	true, video
coverWidth, coverHeight, aspectRatio	1200, 1600, 1.333
authorNickname	public display name
noteId, url	direct link to the note

aspectRatio is included because taller covers occupy more of the feed on mobile — it is a usable explanatory variable for what travels.

Channel breakdown (key-value store, ENGAGEMENT_SUMMARY)

Per channel and overall: notes, notesWithLikes, medianLikes, maxLikes, topShare, videoShare.

topShare is the share of all likes captured by the top 10% of notes. Close to 1 means a few viral notes dominate; lower means attention is spread.

A real measurement across three channels shows why this matters:

Channel	median likes	topShare	videoShare
travel	170	0.554	39%
food	569	0.684	42%
fitness	264	0.812	73%

Fitness is video-first and winner-take-most; travel is neither. Same platform, different game.

Input

{
  "channels": ["travel", "food", "fitness"],
  "maxItemsPerChannel": 40
}

Eleven channels are available: fashion, food, cosmetics, movie, career, love, household, gaming, travel, fitness, video.

Scope and limits — please read

The explore feed is a recommendation feed, not an archive. It returns roughly 24–35 notes per load, the set changes between runs, and this Actor does not scroll. Raising maxItemsPerChannel above that will not produce more notes — add channels instead.

This means the output is a sample of what the channel is surfacing now, which is what makes the per-channel comparison meaningful. It is not a complete list of notes in a category, and should not be used as one.

Keyword search is not supported: Xiaohongshu's search page loads results after mount rather than serving them with the page, so there is nothing to read without driving a logged-in session. This Actor does not log in.

Display names only. You get the public nickname shown on the note, but not the account's internal user id and not the avatar image. Engagement analysis does not need either, and leaving them out keeps the output free of fields that identify and track a person across handle changes.

likes counts are normalized from the site's own abbreviations (4.1万 → 41000). Where a count cannot be read it is returned as null, never 0, so it cannot silently drag a median down.

Pricing

Pay per result — charged only for notes actually delivered to your dataset.

Disclaimer

This is an unofficial tool and is not affiliated with, endorsed by, or sponsored by Xiaohongshu (RED) or its operators. "Xiaohongshu" and "RED" are trademarks of their respective owners and are used here only to describe what this Actor reads. You are responsible for ensuring your use of the collected data complies with applicable law and with the platform's terms.