Xiaohongshu (RED) Channel Scraper — compare categories

Put several Xiaohongshu explore channels side by side and get one row per channel, ranked by how many likes a typical note actually earns.

Categories on Xiaohongshu are not variations of one game. A measurement across three channels:

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. Posting the same way into both is a mistake, and you cannot see that from one channel's feed.

What you get per channel

Field	Example
reachRank	1
channel, notes, notesWithLikes	food, 24, 24
medianLikes, maxLikes	569, 8925
topShare	0.684
videoShare	0.417
tallShare	0.83
uniqueAuthors	23

reachRank is ordered by medianLikes, not total likes. Totals simply reward whichever channel surfaced more notes, which is not the question — you want to know what a typical note earns.

topShare is the share of likes held by the top 10% of notes. High means a few viral notes own the category and a new post is likely to be invisible.

videoShare and tallShare describe the format that is working. Xiaohongshu is a vertical scroll, so taller covers take more of the screen; tallShare is the proportion of notes with an aspect ratio of 1.3 or more.

uniqueAuthors shows whether the sample comes from many creators or a handful. Few authors means a small group is holding the surface.

Summary (key-value store, BENCHMARK_SUMMARY)

channels, channelsWithNotes, medianOfMedianLikes, strongest, and concentrated — channels where the top 10% holds 70% or more of all likes.

Input

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

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

Two or more channels are required. One channel is not a comparison, and the run is rejected rather than returning a single row that answers nothing. If you want the note list for one channel, use Xiaohongshu (RED) Explore Scraper instead.

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. Every channel is therefore measured on a sample of that size — which is exactly what makes the comparison fair, since all channels are sampled the same way.

These are current-form figures, not category averages over time. They are not a complete census of a category and should not be read as one.

Channels that return no notes are still returned as a row with notes: 0 and reachRank: null, so a fetch problem is distinguishable from a genuinely empty result.

Like 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.

Keyword search is not supported: Xiaohongshu's search page loads results after mount rather than serving them with the page. This Actor does not log in.

Display names only. The output is aggregate per channel; where an author is counted, only the public nickname is used, never the account's internal id or avatar.

Pricing

Charged per channel, not per note. One channel is one browser fetch, and the price reflects that this target needs a full browser rather than a plain HTTP request.

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.