Small-World Phenomenon of Global Open-Source Software Collaboration on Github: A Social Network Analysis
Guardat en:
| Publicat a: | Journal of Global Information Management vol. 33, no. 1 (2025), p. 1-25 |
|---|---|
| Autor principal: | |
| Altres autors: | , |
| Publicat: |
IGI Global
|
| Matèries: | |
| Accés en línia: | Citation/Abstract Full Text - PDF |
| Etiquetes: |
Sense etiquetes, Sigues el primer a etiquetar aquest registre!
|
MARC
| LEADER | 00000nab a2200000uu 4500 | ||
|---|---|---|---|
| 001 | 3239807600 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 1062-7375 | ||
| 024 | 7 | |a 10.4018/JGIM.387412 |2 doi | |
| 035 | |a 3239807600 | ||
| 045 | 2 | |b d20250101 |b d20250131 | |
| 084 | |a 10811 |2 nlm | ||
| 100 | 1 | |a Zhang, Guoying |u Midwestern State University, USA | |
| 245 | 1 | |a Small-World Phenomenon of Global Open-Source Software Collaboration on Github: A Social Network Analysis | |
| 260 | |b IGI Global |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a This study employs social network analysis to investigate the dynamics of collaboration regarding open-source software development on GitHub. Specifically, the study focuses on collaboration among various economies as defined by the International Organization for Standardization in ISO 3166-1 (2020). Collaboration data, such as Git pulls and pushes from the GitHub Innovation Graph from 2020 to 2023, were adopted as primary sources. Around 190 eligible economies were included in the analysis based on their collaboration efforts. The study constructed a directed, weighted network to map these collaborations, identify key economies, and validate the small-world phenomenon discussed by Watts and Strogatz in 1998. Network centrality statistics were summarized, and network communities were identified. The small-world phenomenon was validated by benchmarking the small-worldness index proposed by Humphries and Gurney in 2008. Furthermore, this study shows that variations in developer counts, repository volumes, or organization presence do not significantly influence an economy's centrality measures, such as closeness and eigenvector centralities. | |
| 653 | |a Collaboration | ||
| 653 | |a Social networks | ||
| 653 | |a Open source software | ||
| 653 | |a Social dynamics | ||
| 653 | |a International standards | ||
| 653 | |a Social network analysis | ||
| 653 | |a Network centrality | ||
| 653 | |a Software | ||
| 653 | |a Network analysis | ||
| 653 | |a Eigenvectors | ||
| 653 | |a Standardization | ||
| 653 | |a Public domain | ||
| 653 | |a Closeness | ||
| 653 | |a Innovations | ||
| 653 | |a International organizations | ||
| 653 | |a Software development | ||
| 653 | |a Statistics | ||
| 653 | |a Social | ||
| 700 | 1 | |a Schuessler, Joseph H. |u Tarleton State University, USA | |
| 700 | 1 | |a Shao, Chris Y. |u Tarleton State University, USA | |
| 773 | 0 | |t Journal of Global Information Management |g vol. 33, no. 1 (2025), p. 1-25 | |
| 786 | 0 | |d ProQuest |t ABI/INFORM Global | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3239807600/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3239807600/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch |