Hotspot Radar - Trending Topic Tracker

The Problem It Solves

In the landscape of social media, platforms like Weibo, Zhihu, Douyin, Bilibili, and Xiaohongshu each maintain independent trending lists. Manually checking them one by one is time-consuming and makes it difficult to conduct cross-platform trend comparisons or monitor specific topics consistently. For content creators, market researchers, or developers tracking public opinion, there's a need for a tool to automate the aggregation and analysis of this fragmented hot-topic information.

How Hotspot Radar Works

Core Capabilities and Key Steps:

1. Real-Time Data Aggregation: Hotspot Radar fetches data in parallel from the data collection APIs of each platform, pulling real-time lists from Weibo Hot Search, Zhihu Hot List, Douyin Hot Search, Bilibili Hot List, and Xiaohongshu Hot List. It then unifies the data format and sorts it by popularity score.

2. Trend Analysis and Monitoring:

   • Trend Tracking: By comparing current data against historical records stored in the data/history/ directory, the system automatically annotates changes. For example, ↑NEW (newly listed), ↑ (rank up), ↓ (rank down), and ↓OUT (dropped off). It can also identify topics experiencing a rapid surge in popularity.
   • Keyword Monitoring: Users can configure monitoring keywords (e.g., "AI", "exam") in config/monitor.json. Whenever these terms appear on any platform's trending list, the system generates an alert notification.

3. Report Generation:

   • Markdown Reports: Automatically generates a plain-text report featuring cross-platform list comparisons, trend summaries, and monitoring alerts, suitable for pushing to channels like Feishu groups.
   • HTML Visual Reports: Running the command node scripts/index.js html produces an interactive HTML page with a dark theme. This report embeds Chart.js charts, including a bar chart comparing popularity across platforms and a horizontal bar chart for new/rising topics. It also displays platform TOP10 details and monitoring alerts in a card-based layout.

Usage Scope and Considerations

• Data Scope: The tool focuses on aggregating and analyzing list metadata (topic names, ranks, popularity scores). To respect copyrights, it does not deeply crawl or display the specific posts or videos under each topic.
• Configuration Dependencies: Initialization scripts must be run on first use to set up data directories. The scheduled report push feature requires users to pre-configure push channel information (e.g., Feishu webhook) in config/push.json.
• Reliability: It includes an automatic retry mechanism (up to 3 times) for failed data fetches from any single platform, ensuring the failure doesn't disrupt the display of data from other platforms.
• Storage Structure: Historical data is stored following the pattern data/history/{platform}/{YYYY-MM-DD}.json, and trend analysis results are saved in the data/trends/ directory, facilitating retrospective analysis.