# Weibo Hot Search & Brand Trend Tracker (`quanmatrix/weibo-hot-brand-trend-intelligence`) Actor

Track public Weibo hot-search topics and selected brand keywords, returning structured ranks, trend changes and alert-ready signals for social listening and market monitoring.

- **URL**: https://apify.com/quanmatrix/weibo-hot-brand-trend-intelligence.md
- **Developed by:** [Rafael Barreto Haddad](https://apify.com/quanmatrix) (community)
- **Categories:** Social media, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.75 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Weibo Hot Search & Brand Trend Tracker

Track public Weibo hot-search topics and selected brand keywords, returning structured ranks, trend changes and alert-ready signals for social listening and market monitoring.

### Why use this Actor

Brand and research teams need fast, structured Weibo trend alerts with change context rather than a static hot-search list.

### Key features

- Buyer-native inputs aligned to **weibo scraper**.
- Predictable structured output in the default Apify Dataset.
- Pay Per Event pricing tied to measurable result rows or reports.
- Optional MCP connector delivery for downstream automation and AI agents.

### Quick start

Start with this working example and replace the target values with your own:

```json
{
  "trackedKeywords": [
    "AI"
  ],
  "maxResults": 10,
  "onlyMatched": false,
  "previousSnapshot": []
}
```

The Actor writes structured results to the default Apify Dataset and can be used from the Store, API, schedules, Tasks, automations and MCP-compatible AI workflows.

### Input

- `trackedKeywords` — Tracked keywords: Optional brand, competitor, product or topic strings to flag inside the current Weibo hot list.
- `maxResults` — Maximum trends: Maximum hot-search rows returned.
- `onlyMatched` — Only matched tracked keywords: Return only rows containing a tracked keyword.

All integration and advanced analysis fields are optional. The default example is intentionally runnable without configuring MCP or a previous-run baseline.

### Output

The Dataset exposes predictable machine-readable output. Representative fields include `results`.

### Pricing

This Actor uses Pay Per Event. The current factory base price is **$0.002500 per result event**. The Apify Store remains the source of truth for the price and plan/tier details shown to the buyer.

### Use cases

- Run the buyer-ready workflows exposed as Apify Tasks without preparing a custom integration first.
- Use the Actor from API or schedules for recurring collection, comparison or monitoring.
- Feed the structured Dataset output into spreadsheets, databases, automations or AI agents.
- Compare repeat runs when the product supports snapshots or previous-run inputs.

### Automation and AI

Use the same Actor through Apify API, schedules, public Tasks and the Apify MCP server. Outputs are structured for downstream workflows and AI agents rather than requiring manual copy/paste.

### Limitations

- Public websites and upstream APIs can change markup, access rules, rate limits or field availability without notice.
- Fields that are not publicly available are returned as unavailable or omitted rather than fabricated.
- Analytical outputs depend on the quality and coverage of the supplied or collected source data.
- Treat marketplace, reputation, workforce, safety or commercial signals as decision support and validate material decisions against the underlying source evidence.

### Detailed documentation

### Detailed documentation

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### Detailed documentation

Track public Weibo hot-search topics and matched brand keywords, returning structured trend ranks, deltas and alert-ready results.

A static hot-search list is useful for browsing; a monitored, scored list is more useful for operations. This Actor turns Weibo public hot search into repeatable brand and trend intelligence.

### Why use this Actor

This Actor is built for users who need structured evidence and a decision layer rather than a pile of raw HTML. It extracts public-source data, normalizes the records, assigns deterministic scores that can be inspected, and emits compact actions suitable for people, APIs, MCP clients, and autonomous agents. The design favors lightweight HTTP execution where the source permits it and fails explicitly when a source blocks access instead of silently inventing rows. Snapshot input can be reused across scheduled runs to turn one-time extraction into monitoring.

### Key features

- Public Weibo hot-search JSON extraction.
- Rank, heat, labels and tracked-keyword matching.
- Exact rank and heat deltas from a previous snapshot.
- Deterministic trendScore.
- ALERT_TRACKED_BRAND, ALERT_HIGH_PRIORITY, WATCH and MONITOR actions.

### Input

Optionally provide tracked brand/topic keywords, output size, matched-only filtering and a previous snapshot.

### Output

Each row is one hot-search trend with normalized rank/heat evidence, change intelligence and agentAction.

### Example

```json
{
  "trackedKeywords": [
    "AI"
  ],
  "maxResults": 10,
  "onlyMatched": false,
  "previousSnapshot": []
}
```

The default dataset contains one billable decision-ready row per extracted entity. Aggregate summaries and reusable snapshots are stored in the default key-value store when applicable. Scores are deterministic heuristics, not claims of certainty.

### Use cases

- China brand reputation monitoring.
- Newsroom and trend research.
- Campaign/event monitoring.
- Agent-triggered alerts.

### Pricing

Initial benchmark price: US$0.0025 per trend row before tier discounts.

The Actor uses pay-per-event pricing. The primary event is one qualified row written to the default dataset. The product is designed to keep platform cost materially below the event price at normal workloads; the factory rechecks margin from live validation runs before publication.

### Limitations

v1 targets Weibo hot search rather than arbitrary post search. Heat values are platform-provided signals and can change meaning over time.

Public web sources change. A successful extraction today is not a contractual guarantee that a source will preserve the same markup tomorrow. Anti-bot systems, regional network behavior, deleted content, private accounts, and login-only data can reduce coverage. This Actor does not bypass account access controls and does not claim access to private data. Use the output as operational evidence and revalidate high-stakes decisions against the original source.

# Changelog

This Actor's version history is a separate document: https://apify.com/quanmatrix/weibo-hot-brand-trend-intelligence/changelog.md

# Actor input Schema

## `trackedKeywords` (type: `array`):

Optional brand, competitor, product or topic strings to flag inside the current Weibo hot list.

## `maxResults` (type: `integer`):

Maximum hot-search rows returned.

## `onlyMatched` (type: `boolean`):

Return only rows containing a tracked keyword.

## `previousSnapshot` (type: `array`):

Optional prior hot list for exact rank and heat deltas.

## `mcpConnectors` (type: `array`):

Optional MCP connectors authorized in your Apify account. Use them to send or write this Actor result to tools such as Slack, Notion, GitHub, Sentry, Supabase, or another compatible MCP service.

## `mcpToolName` (type: `string`):

Optional exact MCP tool name. Leave blank to let the selected MCP action preset discover a compatible tool automatically.

## `mcpToolArguments` (type: `object`):

JSON object passed to the selected MCP tool. String values may use {{actor_title}}, {{result_summary}}, or {{result_json}} placeholders.

## `mcpFailOnError` (type: `boolean`):

When enabled, an MCP delivery error fails the Actor run. Disabled by default so data extraction and intelligence results remain available even if the external destination is unavailable.

## `mcpActionPreset` (type: `string`):

Choose a safe action pattern. AUTO_SAFE_WRITE discovers a compatible non-destructive write tool automatically; use a specific preset for Slack, GitHub, Notion, or database delivery.

## Actor input object example

```json
{
  "trackedKeywords": [
    "AI",
    "汽车"
  ],
  "maxResults": 50,
  "onlyMatched": false,
  "previousSnapshot": [],
  "mcpToolName": "",
  "mcpToolArguments": {},
  "mcpFailOnError": false,
  "mcpActionPreset": "AUTO_SAFE_WRITE"
}
```

# Actor output Schema

## `results` (type: `string`):

Structured rows from the default dataset.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "trackedKeywords": [
        "AI",
        "汽车"
    ],
    "previousSnapshot": []
};

// Run the Actor and wait for it to finish
const run = await client.actor("quanmatrix/weibo-hot-brand-trend-intelligence").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "trackedKeywords": [
        "AI",
        "汽车",
    ],
    "previousSnapshot": [],
}

# Run the Actor and wait for it to finish
run = client.actor("quanmatrix/weibo-hot-brand-trend-intelligence").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "trackedKeywords": [
    "AI",
    "汽车"
  ],
  "previousSnapshot": []
}' |
apify call quanmatrix/weibo-hot-brand-trend-intelligence --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,quanmatrix/weibo-hot-brand-trend-intelligence"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/TBpAjqnHU93lSCYRa/builds/QFuZLcjshW4zdWi94/openapi.json