BlackCat Scraper 黑猫投诉 (No Cookie) — China Consumer Complaints

Extract real-time Chinese consumer complaints, refund disputes, product defect reports, and brand crisis signals from Sina BlackCat (新浪黑猫投诉 / tousu.sina.com.cn) — China's largest public consumer-rights and dispute-resolution platform with 38M+ verified complaints.

Built for Wall Street alt-data equity research, multinational brand PR & legal teams, supply-chain due diligence, and AI/LLM risk-monitoring pipelines (n8n, Make, Dify, Claude MCP). 100% no login, no cookies, and no VPN required. Users on the Apify Free plan ($5 monthly credit) can extract up to 1,111 BlackCat complaint records per month for free.

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What Can This BlackCat Scraper Do? (Features)

BlackCat Scraper Capability	Built-In Advantage
Brand & Keyword Search (searchQuery)	Search consumer complaints about any domestic or international brand via our built-in managed session pool and signed API (tousu.sina.com.cn/api/index/s).
Nationwide Live Complaint Feed	Leave searchQuery empty to stream the latest consumer disputes across all industries in China (tousu.sina.com.cn/api/index/feed).
Auto EN ↔ ZH Brand Localization	Type an English brand name (e.g., Tesla, Apple, Luckin, Starbucks, Nike) and the scraper automatically translates and queries its official Chinese name (特斯拉, 苹果, 瑞幸咖啡, 星巴克, 耐克).
Standardized English Status (statusEn)	Automatically maps Chinese dispute stages into standardized English statuses (pending_assignment, in_progress, replied, completed, closed).
Built-In Complaint Sentiment Scoring	Zero-RAM Chinese/English sentiment engine with negation reversal tags every complaint with sentiment (negative / neutral / positive) and sentimentScore (-1.0 to +1.0).
256 MB RAM Real-Time Streaming	Streams complaint records to your Apify Dataset in real-time batches of 10 rows on just 256 MB RAM, supporting scheduled monitoring (deltaMode), REST API, and one-click JSON, CSV, Excel, or Parquet exports.

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How to Scrape BlackCat (黑猫投诉) in 3 Easy Steps

1. Enter a Brand or Keyword (searchQuery) — Type any company, brand, or product in English or Chinese (e.g., Tesla, Luckin, 瑞幸咖啡, 携程), or leave it empty to capture the nationwide live complaint feed.
2. Set maxResults — Choose how many BlackCat complaints to extract (from 1 to 5,000).
3. Click "Start" — Download your structured consumer complaint dataset in JSON, CSV, or Excel, or connect directly to n8n, Make, Google Sheets, or Claude MCP.

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BlackCat Scraper Use Cases

Buyer Profile	BlackCat Consumer Intelligence Use Case
Hedge Funds & Equity Research Desks	Track complaint velocity, refund demand spikes (退款), and resolution rates (statusEn) as an early warning alt-data signal on Chinese consumer & EV tickers (BYD, Tesla, NIO, Luckin, PDD, Alibaba, Meituan)
Global Brand PR & Crisis Teams	Detect product safety issues, counterfeit reports, and customer service failures in China before they escalate to Weibo Hot Search
Legal, Compliance & ESG Analysts	Audit corporate consumer-rights responsiveness and dispute patterns across Chinese subsidiaries and e-commerce storefronts
AI / LLM Risk & Financial Agents	Ground autonomous research agents in live Chinese consumer dispute records via REST API or Claude MCP

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Input

All parameters are available in the Input tab. Below are the primary configuration fields and JSON input examples:

Input Field	Type	Description
searchQuery	string	Brand, company, or product keyword in English or Chinese (e.g., "Tesla", "瑞幸咖啡"). Leave empty "" for the nationwide live complaint feed.
autoLocalize	boolean	Automatically translates English brand names into Simplified Chinese (default: true).
searchAliases	array	Additional sub-brands or product keywords to merge and deduplicate into the same run.
maxResults	integer	Maximum number of BlackCat complaints to return (1 to 5,000, default: 50).
sentimentAnalysis	boolean	Attaches sentiment polarity and sentimentScore (-1.0 to +1.0) to every complaint (default: true).
deltaMode	boolean	Remembers scraped complaint sn IDs across scheduled runs so you only pay for newly filed complaints (default: false).

1. Brand-Specific BlackCat Complaint Search (JSON)

{
  "mode": "complaints",
  "searchQuery": "Tesla",
  "autoLocalize": true,
  "searchAliases": ["Model Y", "Model 3"],
  "maxResults": 100,
  "sentimentAnalysis": true,
  "deltaMode": false
}

2. Nationwide Live Consumer Complaint Feed (JSON)

{
  "mode": "complaints",
  "searchQuery": "",
  "maxResults": 200,
  "sentimentAnalysis": true
}

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Output

Each scraped complaint is stored in your Apify Dataset with the following structured fields (matching the "Tesla" search input above):

{
  "mode": "complaints",
  "sn": "17402449965",
  "company": "特斯拉客户支持",
  "title": "特斯拉门店充电桩计费异常且客服未按承诺退还差价",
  "appeal": "退款,改善服务,作出解释",
  "text": "本人于2026年10月22日在超级充电站充电，账单多扣取超时占用费，联系特斯拉客服核实后至今未退回...",
  "summary": "本人于2026年10月22日在超级充电站充电，账单多扣取超时占用费，联系特斯拉客服核实后至今未退回...",
  "sentiment": "negative",
  "sentimentScore": -0.78,
  "statusEn": "in_progress",
  "scrapedAt": "2026-10-24 16:32:10 UTC"
}

Output Field Definitions

• sn: Unique BlackCat complaint serial number (used for deduplication in deltaMode).
• company: Official name of the complained-against company or brand (投诉对象).
• title: Headline of the consumer complaint.
• appeal: Specific consumer demands (投诉要求, e.g., 退款 refund, 赔偿 compensation, 道歉 apology).
• text / summary: Clean HTML-stripped complaint summary text.
• statusEn: Standardized dispute progress (pending_assignment, in_progress, replied, completed, closed).
• sentiment / sentimentScore: Polarity label and normalized severity score (-1.0 to +1.0).

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Automated Daily Brand Crisis Monitoring (Schedules & Delta Mode)

Set up a 24/7 automated brand complaint monitor in 2 minutes:

1. In Apify Console → Schedules → Create new schedule, select axon-studio/blackcat-scraper and set your cron frequency (e.g., hourly 0 * * * * or daily 0 8 * * *).
2. Set deltaMode: true in your input JSON. The Actor stores up to 10,000 scraped sn IDs in your Key-Value Store (DELTA_SEEN_IDS) and skips previously delivered complaints on future runs—so you only pay for brand-new disputes.

Python, JavaScript & One-Line REST API Integration

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_API_TOKEN")
run = client.actor("axon-studio/blackcat-scraper").call(run_input={
    "mode": "complaints",
    "searchQuery": "Tesla",
    "autoLocalize": True,
    "maxResults": 100,
    "sentimentAnalysis": True,
})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["sn"], item["company"], item["statusEn"], item["title"])

curl -X POST "https://api.apify.com/v2/acts/axon-studio~blackcat-scraper/run-sync-get-dataset-items?token=YOUR_APIFY_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"mode":"complaints","searchQuery":"Tesla","maxResults":50,"sentimentAnalysis":true}'

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How Much Does It Cost to Scrape BlackCat? (Pricing)

$4.50 per 1,000 complaints ($0.0045 per item) + $0.02 per Actor start (Pay-Per-Event)

• Free Plan Credits: Every Apify account includes $5.00 in free monthly credits, covering up to 1,111 BlackCat complaint records every month for free.
• Volume Discounts: Automatic lower unit prices for Apify Bronze / Starter, Silver / Scale, and Gold / Business plan subscribers.
• No Server Compute Fees: Memory and CPU usage are fully included in the Pay-Per-Event rate.
• Typical Run Costs: 50 brand complaints = $0.245 · 200 brand complaints = $0.92 · 1,000 complaints = $4.52.

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FAQ & Legal Compliance

Do I need a Sina Weibo or BlackCat login cookie?

No. This BlackCat Scraper uses a built-in managed session pool and SHA-256 request signing automatically.

Is it legal to scrape BlackCat consumer complaints?

This Actor extracts publicly visible consumer dispute summaries from tousu.sina.com.cn and does not access private user accounts. Under GDPR and PIPL, ensure you have a lawful basis for market research or compliance analytics. Not affiliated with Sina Corporation.

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