Twitch Streaming Graph Analysis - Part 2

In Part 2 of a three-part blog series, the focus is on implementing the frontend of a Twitch streaming graph analysis application using React and D3.js. This installment guides readers through setting up a React app to work alongside a Flask backend, using Semantic UI for styling. It includes instructions on configuring a proxy for seamless communication with the backend, Dockerizing the application, and creating custom hooks to enable D3.js interaction for graph visualization. The blog also details fetching and displaying data, such as game statistics and streamer rankings, using API requests, and highlights the use of powerful query modules like PageRank and Betweenness Centrality to enhance data visualization. The author encourages readers to engage with the community and look forward to Part 3, which will cover streaming data integration with Kafka.

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