Meme Quantum Pulse is a research-grade web application that demonstrates QEGNN (Quantum-Inspired Entangled Graph Neural Network) for real-time meme and post virality prediction.
The system uses a hybrid classical + quantum-inspired AI pipeline (simulated) to predict whether a social media post is likely to go viral, providing confidence levels, latency data, and explainability metrics.
Important
This deployment uses simulated data and models for academic demonstration and research purposes.
- Real-time Prediction: Instant Viral / Non-Viral classification.
- Hybrid Metrics: Probability scores alongside inference latency (ms).
- Dual-Mode Toggle: Compare Classical GNN vs. QEGNN performance.
- Explainability (XAI): - Graph Influence Scores
- Entanglement-based Correlation Scores
- Analytics Dashboard: Visualizing information diffusion patterns.
- Research Transparency: Integrated IEEE-defensible ethics notices.
- Nodes: Users/Posts encoded as quantum-inspired state vectors.
- Edges: Entanglement-like correlations in information diffusion.
- Quantum Layer: Variational circuits (simulated via PennyLane).
- Output: Virality probability + Confidence interval + Latency.
The project evaluates if quantum-inspired representations improve scalability and efficiency over standard GNNs in complex social graphs.
- User Input: Textual content and metadata.
- Feature Encoding: High-dimensional vector transformation.
- Quantum-Inspired Layer: Simulated variational circuit processing.
- Graph Neural Network: Information propagation through the network.
- Output Engine: Prediction results and explainability data.
- Frontend: React, TypeScript, Tailwind CSS, shadcn/ui.
- Platform: Lovable
- AI/ML Core: Python, PyTorch Geometric, PennyLane, NetworkX.
# Clone the repository
git clone <YOUR_GIT_URL>
# Navigate to project directory
cd meme-quantum-pulse
# Install dependencies
npm install
# Start development server
npm run dev