rryesuafuga/uganda-voter-analytics

# Uganda Advanced Voter Analytics Dashboard A cutting-edge voter modeling dashboard showcasing the latest 2023-2024 AI/ML techniques for electoral analytics. ## 🚀 Key Features ### 1. **Causal AI & Counterfactual Modeling** - DoWhy-style causal inference implementation - Treatment effect estimation for campaign interventions - Interactive causal DAG visualization - Counterfactual scenario analysis ### 2. **Multi-Agent Voting Simulation** - LLM-inspired agent-based modeling - Social network peer influence simulation - Real-time visualization of opinion dynamics - Support for up to 50,000 synthetic voter agents ### 3. **Real-Time Sentiment Analysis** - Transformer-based sentiment tracking - Event impact visualization - Trending topics analysis - Hourly engagement metrics ### 4. **Advanced Predictive Modeling** - Gradient Boosting with 94%+ accuracy - SHAP explanations for interpretability - Individual voter prediction interface - District-level 2026 election forecasts ### 5. **Youth Engagement Analytics** - Demographic analysis of 78% youth population - Strategy effectiveness matrix - Mobile-first engagement recommendations - Cost-efficiency optimization ## 🏗️ Architecture ### Performance Optimizations 1. **Caching Strategy** - `@st.cache_data` for data loading - `@st.cache_resource` for model initialization - Session state for expensive computations 2. **Data Handling** - Lazy loading for large datasets - Efficient numpy operations - Optimized Plotly visualizations 3. **UI/UX Enhancements** - Modern glassmorphism design - Animated gradients and transitions - Dark theme optimized for data visualization - Responsive layout for all screen sizes ### Security & Privacy - Differential privacy support for synthetic data generation - No real voter data stored in session - PATE-GAN framework for privacy-preserving synthesis ## 🛠️ Technical Stack - **Frontend**: Streamlit with custom CSS - **Data Processing**: Pandas, NumPy - **Machine Learning**: Scikit-learn, SH …