AI-Enhanced Social Network Analysis

The rapid growth of social media platforms has produced vast and complex interaction networks that demand intelligent analytical systems. This study presents the AI Social Network Analyzer, an integrated platform that combines graph theory and artificial intelligence to understand and predict social dynamics. The system utilizes advanced algorithms such as Union-Find, PageRank, Greedy Modularity, and Centrality metrics to detect communities, identify key influencers, and map relational structures. Complementing these, AI-driven modules powered by Google Gemini perform sentiment classification, topic extraction, and trend prediction to assess content behavior. Data from Reddit is processed through automated pipelines using Python, NetworkX, and Streamlit, producing real-time visualizations and interactive dashboards. Experimental analyses demonstrate the platform’s ability to uncover hidden community patterns, forecast viral content, and quantify user influence with high interpretability. The proposed framework illustrates the potential of hybrid AI-graph approaches for social intelligence, offering a scalable foundation for future multi-platform social analytics and trend forecasting systems.