Disclaimer: on AI usage

This project was developed with the assistance of OpenAI's GPT-4 and 5. The frontend code, in particular, was almost entirely generated by the model based on the requirements provided (I have only limited knowledge in js or html). The python-based backend code, in contrast, was almost entirely written by me, with the model providing suggestions and improvements upon request.

User Journey Network Visualization

This project visualizes user journey networks using Flask (backend) and Cytoscape.js (frontend). It simulates or loads user navigation data, builds a network graph, and provides an interactive dashboard for exploration.

It is a prototype that is thought as a collaborative project between data scientists and web developers to create a tool for analyzing user journeys on websites or applications.

Features

• Interactive network visualization (Cytoscape.js)
• Device and network type filtering
• Shortest path highlighting between nodes
• Weight threshold slider for edge filtering
• Hover tooltips for nodes and edges
• time dependent visualization of network metrics

Setup

1. Install Python dependencies:

   pip install flask flask-caching pandas numpy networkx scipy matplotlib

2. Run the Flask app:

   python app.py

3. Open your browser at http://localhost:5000

File Structure

• app.py - Flask backend serving the API and dashboard
• app_helpers/ - Helper modules for data and network logic (backend)
• static/ - Frontend files (HTML, JS, CSS)

Customization

• Adjust data generation or connect to real data in app_helpers/get_data.py
• Modify network logic in app_helpers/network_class.py
• Update frontend UI in static/dashboard.html and static/network_logic.js

License

MIT License