🔍 Twitter Network Analytics Demo 🔍
A web application with backend in Flask and frontend in React and D3.js that uses Memgraph to ingest real-time data scraped from Twitter. Data is streamed via Kafka and stream processing is performed with Memgraph.
App architecture
Data model
Prerequisites
You will need:
- Docker
- Docker Compose (included with Docker Desktop on Windows and macOS)
Running the app
With a bash script
You can start everything but frontend by running the bash script:
bash run_docker.sh
After that, in other window run the frontend app with:
docker-compose up frontend-app
Manually using Docker Compose
If you want to start the app without using the bash script, then:
1. Remove possibly running containers:
docker-compose rm -fs
2. Build all the needed images:
docker-compose build
3. Start the Kafka, Zookeeper and Memgraph MAGE services:
docker-compose up -d core
4. Start the data stream:
docker-compose up -d stream
5. Start the backend application:
docker-compose up backend-app
6. Start the frontend application in new terminal window:
docker-compose up frontend-app
The React application will be running on http://localhost:3000.
Choose the visualization
In the dropdown, select the algorithm you want to check out, and click on the 'Select algorithm' button.
Default algorithm is Community detection:
The other algoritm is PageRank:
