Dynamic Public Opinion Hotspot Analysis System Architecture Based on Multi-Source Fusion

With the rapid proliferation of social media platforms, the impact of online public opinion on social governance has become increasingly pronounced. To overcome the limitations of traditional public opinion analysis methods-particularly their poor real-time performance and insufficient data coverage-this study proposes a dynamic public opinion hotspot analysis system architecture based on multi-source fusion, which integrates multi-platform data streams utilizing automated collection, intelligent sentiment analysis, and geospatial mapping technologies. The system enables real-time monitoring, adaptive early-warning with configurable thresholds, and AI-driven visual analytics. This research provides government agencies and enterprises with an efficient public opinion monitoring tool, demonstrating significant practical value for enhancing crisis response capabilities and improving social governance precision through data-driven insights.