# Bilibili Creator, Video & Danmaku Analyzer (`quanmatrix/bilibili-creator-danmaku-intelligence`) Actor

Analyze Bilibili popular videos or BV IDs and return creator, video, danmaku and engagement metrics with trend scoring and repeat-run change tracking for creator research.

- **URL**: https://apify.com/quanmatrix/bilibili-creator-danmaku-intelligence.md
- **Developed by:** [Rafael Barreto Haddad](https://apify.com/quanmatrix) (community)
- **Categories:** Social media, Videos
- **Stats:** 2 total users, 1 monthly users, 88.9% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.45 / 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

## Bilibili Creator, Video & Danmaku Analyzer

Analyze Bilibili popular videos or BV IDs and return creator, video, danmaku and engagement metrics with trend scoring and repeat-run change tracking for creator research.

### Quick start

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

```json
{
  "mode": "popular",
  "maxResults": 20,
  "sortBy": "trendScore",
  "minViews": 0,
  "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

- `mode` — Mode: Choose public popular-feed monitoring or enrich explicit Bilibili BV video IDs.
- `bvids` — Bilibili BV IDs: BV video IDs to enrich when mode is videos.
- `maxResults` — Max results: Maximum video rows returned in one run.
- `sortBy` — Decision sort: Sort normalized results by decision score, views, danmaku intensity, or engagement rate.
- `minViews` — Minimum views: Discard rows below this public view count.

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 **$0.003500 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

### Detailed documentation

Turn public Bilibili video activity into decision-ready creator and audience intelligence. This Actor monitors the public popular feed or enriches explicit BV video IDs, then normalizes raw engagement counters into comparable metrics that are easier to use in monitoring systems, dashboards, research pipelines, and AI-agent workflows.

### Why use this Actor

Most Bilibili scrapers stop at extraction: views, likes, comments, danmaku counts, creator names, and video metadata. Those fields are useful, but teams still have to calculate which videos are truly over-performing, whether audience reaction is unusually intense, and what changed since the previous run. This Actor adds that decision layer directly to every output row.

It is designed for repeatable monitoring. Run it once, keep the generated `SNAPSHOT`, and send that snapshot back on a later run. The Actor then calculates exact view, like, and danmaku deltas and combines them with current engagement signals into a deterministic `trendScore` and `agentAction`.

### Key features

- Public Bilibili popular-feed monitoring without login or cookies.
- Explicit BV-ID enrichment for videos you already track.
- `danmakuIntensity`: danmaku messages normalized per 1,000 views.
- `engagementRate`: combined likes, coins, favorites, replies, danmaku, and shares relative to views.
- Snapshot-to-snapshot `viewDelta`, `likeDelta`, and `danmakuDelta`.
- Deterministic `trendScore` for comparable prioritization across runs.
- Agent-ready actions such as `ALERT_BREAKOUT`, `WATCH_CREATOR`, `MONITOR`, and `LOW_PRIORITY`.
- Lightweight 256 MB default runtime and Limited Permissions.
- Structured dataset view plus reusable `SNAPSHOT` and `AUDIENCE_SUMMARY` key-value outputs.

### Input

`mode` can be `popular` or `videos`. Use `popular` for current public popular-feed monitoring. Use `videos` together with `bvids` when you want to enrich a defined watchlist. `maxResults` caps output volume, `sortBy` chooses the business ranking signal, `minViews` removes low-reach rows, and `previousSnapshot` enables exact momentum calculations.

### Example

```json
{
  "mode": "popular",
  "maxResults": 20,
  "sortBy": "trendScore",
  "minViews": 0,
  "previousSnapshot": []
}
```

For a watchlist run:

```json
{
  "mode": "videos",
  "bvids": ["BV1sHb56xEhC"],
  "maxResults": 10,
  "sortBy": "danmakuIntensity",
  "previousSnapshot": []
}
```

### Output

Each dataset row contains video and creator identity, public engagement counters, normalized audience metrics, trend scoring, agent action, publish time, scrape time, and optional deltas when a previous snapshot is supplied. This means downstream systems can compare current reach with audience intensity rather than treating every raw count as equally meaningful.

### Use cases

Use the Actor for China creator monitoring, gaming and anime trend research, campaign reaction tracking, competitive attention analysis, influencer shortlisting, daily or weekly audience benchmarks, product-launch monitoring, crisis/reputation spikes, or automated social-listening agents that need compact and deterministic signals.

Twenty task blueprints are included for distinct commercial monitoring intents such as breakout detection, danmaku intensity, engagement quality, high-view videos, gaming, anime, esports, creator momentum, campaign pulse, launch reaction, weekly benchmarking, competitive attention, and agentic monitoring.

### Pricing

The product uses pay-per-event pricing around one primary measurable result: one enriched Bilibili audience-intelligence row. Pricing is tiered through FREE, BRONZE, SILVER, and GOLD levels when supported by the Apify account configuration. The design avoids charging separate events for the derived analytics fields on the same result row.

### Data source and reliability

Version 1 uses Bilibili public HTTP endpoints that were validated from the QuanMatrix production host before build. The default popular endpoint currently returns video IDs, creator identity, publication time, and public engagement statistics without requiring account credentials. Public endpoints can change or throttle, so the Actor fails visibly rather than returning fabricated rows.

### Limitations

This version intentionally focuses on public popular-feed data and explicit BV IDs. It does not claim to provide raw danmaku text, private data, account-only information, or authenticated creator analytics. `UNKNOWN` competitor capabilities are not treated as missing features in our internal competitive gate, and the product is promoted only when its own verified advantages remain valid.

### Monitoring workflow

1. Run the Actor using `popular` or a BV-ID watchlist.
2. Export or store the `SNAPSHOT` value from the run.
3. Supply that array as `previousSnapshot` on the next run.
4. Use deltas, `trendScore`, and `agentAction` to prioritize creators or videos.
5. Schedule subsequent runs at the cadence appropriate to the campaign or market being monitored.

# Changelog

This Actor's version history is a separate document: https://apify.com/quanmatrix/bilibili-creator-danmaku-intelligence/changelog.md

# Actor input Schema

## `mode` (type: `string`):

Choose public popular-feed monitoring or enrich explicit Bilibili BV video IDs.

## `bvids` (type: `array`):

BV video IDs to enrich when mode is videos.

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

Maximum video rows returned in one run.

## `sortBy` (type: `string`):

Sort normalized results by decision score, views, danmaku intensity, or engagement rate.

## `minViews` (type: `integer`):

Discard rows below this public view count.

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

Optional normalized prior output for exact view, like, and danmaku 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
{
  "mode": "popular",
  "bvids": [],
  "maxResults": 20,
  "sortBy": "trendScore",
  "minViews": 0,
  "previousSnapshot": [],
  "mcpToolName": "",
  "mcpToolArguments": {},
  "mcpFailOnError": false,
  "mcpActionPreset": "AUTO_SAFE_WRITE"
}
```

# Actor output Schema

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

Structured Bilibili audience-intelligence 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 = {
    "bvids": [],
    "previousSnapshot": []
};

// Run the Actor and wait for it to finish
const run = await client.actor("quanmatrix/bilibili-creator-danmaku-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 = {
    "bvids": [],
    "previousSnapshot": [],
}

# Run the Actor and wait for it to finish
run = client.actor("quanmatrix/bilibili-creator-danmaku-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 '{
  "bvids": [],
  "previousSnapshot": []
}' |
apify call quanmatrix/bilibili-creator-danmaku-intelligence --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,quanmatrix/bilibili-creator-danmaku-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/vdYsPbocbY5DaG7nJ/builds/OlihXvbrjUvgd2YK4/openapi.json