Xiaohongshu Comment Keyword & Consumer Voice

Turn Xiaohongshu / RedNote comments into an evidence-linked consumer research report.

This Actor does more than export raw comments. It shows what consumers repeatedly ask, worry about, compare, consider as alternatives, and expect from content or products. Every conclusion keeps source comment IDs and note URLs so a researcher can audit the evidence.

What the report includes

• comment keyword frequency and linked evidence;
• recurring consumer questions;
• needs and purchase motivations;
• concerns such as efficacy, safety, ingredients, price, usage, trust, and channels;
• known brand, product, ingredient, and competitor mentions;
• direct comparison comments and alternatives;
• usage scenarios such as commuting, travel, family, exercise, or meal timing;
• transparent cue-based sentiment distribution;
• ranked content opportunities backed by real comments;
• optional regulated-claim screening for health and other sensitive topics;
• optional normalized source-comment archive inside the report.

Four ways to run it

1. No-Cookie demo

Choose demo to see the full output immediately. The sample is clearly marked as demo data.

2. Search a topic and analyze comments

Choose keywordResearch, enter a Xiaohongshu search query, and provide your own session Cookie in the secret field. The Actor finds notes, collects their comments and replies, and creates one report.

3. Analyze selected notes

Choose noteResearch, paste note URLs or IDs, and provide your own session Cookie. Preserve xsec_token in shared URLs when available.

4. Analyze comments you already have

Choose uploadedComments and paste comments from another Actor or your own file. No Cookie is required. Strings and common JSON fields such as text, content, comment, commentId, noteId, noteUrl, authorName, and likes are recognized.

Example input: uploaded comments

{
  "mode": "uploadedComments",
  "topic": "blood glucose management supplements",
  "uploadedComments": [
    {
      "commentId": "c1",
      "noteId": "n1",
      "noteUrl": "https://www.xiaohongshu.com/explore/n1",
      "text": "这个真的有效吗？和产品乙相比哪个好，有没有副作用？",
      "likes": 36
    },
    {
      "commentId": "c2",
      "noteId": "n2",
      "text": "价格贵不贵？我更想先控制饮食和运动。"
    }
  ],
  "commentKeywords": ["副作用", "价格", "饮食", "运动"],
  "knownEntities": ["产品甲", "产品乙"],
  "competitorNames": ["产品乙"],
  "regulatedTopic": true
}

Pricing

$4.99 per report analyzing up to 100 comments. The 100-comment limit applies across all selected notes and includes replies. For more than 100 comments, run another report. Failed collection, no-result runs, and inputs that produce no usable comments do not create the paid report event. Platform usage is included in the customer-facing event price; the developer absorbs the underlying Apify usage costs. A minimal Actor-start event may still apply as shown in the Store pricing table.

Cookie and privacy model

• The developer does not publish or share a personal Cookie.
• Live modes use the customer's own Cookie from Apify's secret input field.
• The Cookie is never included in dataset output or application logs.
• Uploaded-comment mode and demo mode require no Cookie.
• Use only accounts, sessions, and data you are authorized to use.

Analysis method and limitations

The first version uses deterministic, evidence-linked Chinese cue dictionaries rather than an LLM. Counts describe the collected sample, not all Xiaohongshu users. Sentiment and theme labels can be wrong or incomplete, so important decisions should be checked against the included source comments.

Live Xiaohongshu collection can fail when a session expires, a security token is missing, the platform changes an endpoint, a result is restricted, or anti-automation controls are triggered. Residential proxy and conservative limits can improve reliability but do not guarantee access.

This Actor is a research aid, not legal, medical, financial, or regulatory advice. Do not treat consumer comments as proof of product efficacy or safety.