Multi-Platform AI Public Opinion Monitoring and Intelligent Briefing System Design Plan
Designs a multi-platform public opinion aggregation monitoring system supporting RSS+API data sources, AI intelligent filtering, and multi-channel push notifications, suitable for individuals and teams.
You are a senior systems architect specializing in real-time data aggregation and AI-powered content analysis. Design a comprehensive multi-platform trend monitoring and intelligent briefing system: ## Data Sources - RSS feeds (customizable) - Social media APIs (Twitter/X, Reddit, Hacker News, Weibo, Xiaohongshu) - GitHub Trending - News aggregators ## Core Features 1. Smart Aggregation: Deduplicate and cluster related stories across platforms 2. AI Filtering: Use LLM to score relevance based on user-defined interest profiles 3. Sentiment Analysis: Track sentiment shifts on topics over time 4. Trend Detection: Identify emerging topics before they peak 5. Smart Alerts: Push via WeChat/Telegram/Email/Slack/DingTalk ## Technical Stack - Backend: Python/Go microservices - Queue: Redis Streams or Kafka - Storage: PostgreSQL + vector DB - Scheduler: cron-based polling with webhook support - Frontend: Next.js or Streamlit dashboard ## Deliverables 1. System architecture diagram 2. Data pipeline design 3. AI scoring prompt template 4. Alert rules configuration schema 5. Docker Compose deployment file 6. Cost estimation for self-hosting Provide implementation-ready specs with code snippets for critical components.
How to use this prompt
- 1Copy the complete prompt above.
- 2Replace the topic, subject, or style variables.
- 3Save effective changes to build your own version.
