Data Skeptic Github Collaboration Network
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Nov 11, 2024 Behnaz Moradi-Jamei, an assistant professor at James Madison University specializing in network data science, delves into the intricate web of GitHub contributors. She unveils her groundbreaking analysis of a sprawling network connecting 700,000 developers through shared contributions. The conversation touches on community detection algorithms, ethical considerations in network analysis, and innovative methodologies for enhancing collaboration insights. Behnaz emphasizes the importance of adapting algorithms to reflect real-world developer interactions, pushing the boundaries of open-source community understanding.
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GitHub Collaboration Network Analysis
- Behnaz Moradi-Jamei's team analyzed 1.8 million GitHub users and their interactions, focusing on open-source projects.
- They used a Julia package called Ghost to collect data from 2008-2019, resulting in a network of 177 million edges.
Defining Nodes and Edges
- GitHub users become nodes, and an edge connects them if they contribute to the same repository.
- This network represents collaborations, not just individual contributions.
Improving Community Detection Accuracy
- Traditional methods didn't capture GitHub collaborations effectively.
- A "renewal non-backtracking walk" approach was developed, emphasizing cyclic collaboration structures.