Fake content threatens Xiaohongshu monetization

This is a monetization risk as much as a moderation risk, because Xiaohongshu sells ads against user trust, not just user attention. People come to the app for purchase advice that feels like it came from a real person who actually tried the product. When fake personas, mass produced notes, and unlabeled AI posts spread at scale, the feed starts to feel less like firsthand recommendation and more like spam, which weakens both creator credibility and advertiser demand.1 2 3 4

• The scale matters. In H1 2025, Xiaohongshu said it handled about 3.2M fake notes, 10K fake persona accounts, and 600K low quality AI generated notes. Those numbers show this is not edge case cleanup, it is a core operating burden on one of the platform’s main products, the note feed itself.1 2
• The pressure is higher on Xiaohongshu than on a pure entertainment feed because users often open it before spending money. Its business is still heavily ad driven, while many users discover products on Xiaohongshu and then buy on Tmall or Taobao. That makes trust in recommendation quality a direct input into revenue.3 4
• Platforms usually solve this tradeoff by accepting more moderation friction as they become more ad dependent. Reddit followed a similar path, tightening content standards to become safer for advertisers even when that created backlash from parts of its user base. Xiaohongshu’s AI labeling and distribution limits fit that same playbook.5

The next step is a feed where authenticity becomes part of ranking, not just a policy layer. Xiaohongshu is likely to push creators toward clearer disclosure, more proof of real use, and less synthetic volume. That should make posting harder at the margin, but it also protects the trust loop that keeps the app valuable to brands and shoppers.1 2 4