A web-based Minimum Viable Product (MVP) designed to analyze, structure, and visualize complex relationships within the media landscape in real-time.
Traditional relational databases (SQL) often reach performance limits when querying deeply nested relationships between journalists, media outlets, and topics. The Journalist Intelligence Graph solves this problem by using graph database technology to represent media entities as nodes and their connections as edges, enabling fast, interactive network analysis.
- Graph-Based Data Modeling: Native representation of complex relations between journalists, news organizations, and target topics.
- Real-Time Visualization: Interactive graph explorer for intuitive navigation through media networks.
- Asynchronous Processing: High-performance API backend for efficient data filtering and retrieval.
- Cross-Platform UI: Modern, responsive web interface built for smooth performance in the browser.
- Backend: Python, FastAPI
- Database: Neo4j (Graph Database), Cypher
- Frontend: Flutter Web (Dart)
- Architecture: Layered Architecture / REST API
- Frontend (Flutter Web): Handles data visualization, user interaction, and dynamic graph rendering.
- Backend (FastAPI): Acts as the API layer, managing business logic and asynchronous communication with the database.
- Database (Neo4j): Stores and executes highly optimized graph queries for connected data.
- Python 3.10+
- Flutter SDK
- Neo4j Database Instance (Local or Neo4j Aura)
- Clone the repository:
git clone https://github.com/Kirillix123/Journalist-Intelligence-Graph.git cd Journalist-Intelligence-Graph - Backend Setup (FastAPI)
cd backend python -m venv venv source venv/bin/activate # On Windows use: venv\Scripts\activate pip install -r requirements.txt
- Frontend Setup (Flutter Web)
cd frontend flutter pub get flutter run -d chrome