How to Analyze Commits in a GitHub Social Network in Real-Time?

GitHub, often seen as both a software development platform and a social network, offers a dynamic dataset that can be analyzed in real-time using streaming data and graph algorithms like PageRank and community detection through tools such as Memgraph. The blog explores the use of these algorithms to identify influential users and detect communities within GitHub's social structure, highlighting the challenges of running computationally expensive algorithms on constantly changing datasets. To address these challenges, dynamic versions of these algorithms, which update only affected nodes, are utilized via the MAGE graph algorithm library. The process involves setting up Memgraph to ingest GitHub data streams, running queries to analyze the data, and creating triggers to automate updates as new data arrives. This approach allows for intuitive and efficient real-time data analysis, making it possible to derive strategic insights from the network's social dynamics.