Community Formation and Detection on GitHub Collaboration Networks

Nov 15, 2021·
Behnaz Moradi Jamei
,
Brandon Lee Kramer
Dr. José Bayoán Santiago Calderón
Dr. José Bayoán Santiago Calderón
,
Gizem Korkmaz
· 0 min read
Abstract
This paper studies community formation in open-source software collaboration networks using a large-scale historical dataset of GitHub users and repositories. We combine Renewal-Nonbacktracking Random Walks with Louvain community detection to better identify small collaboration teams and characterize factors associated with community formation, including geography and programming language specialization.
Type
Publication
Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Status
Peer-reviewed
publications
Dr. José Bayoán Santiago Calderón
Authors
Dr. José Bayoán Santiago Calderón (he/him)
Research Economist

José Bayoán Santiago Calderón is a senior research economist in the national economic accounts research group at the U.S. Bureau of Economic Analysis. Before joining the federal statistical system, Dr. Santiago Calderón had years of experience in the private sector as a research scientist at various companies. Bayoán also held academic appointments with the Biocomplexity Institute and Initiative at the University of Virginia, where he started his career in public service.

His research has centered on improving decision-making. His transdisciplinary research approach has enabled him to routinely collaborate across disciplines and develop a diverse set of domain knowledge and methodological toolset. He also participates in various open-source software communities (e.g., JuliaLang) and civic activism (e.g., Code4PR, Mentes Puertorriqueñas en Accion).

In his non professional life, Bayoán enjoys spoiling his dog (Sadaharu), playing video games, watching TV, reading manga, and programming.

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