Abstract
Open source software development platforms are natural laboratories for studying the diffusion of innovation across human populations, enabling us to better understand what motivates people to adopt new ideas. For example, GitHub, a software repository and collaborative development tool built on the Git distributed version control system, provides a social environment where ideas, techniques, and new methodologies are adopted by other software developers. This paper proposes and evaluates a popularity-based model of the diffusion of innovation on GitHub. GitHub supports a mechanism, forking, for creating personal copies of other software repositories that can be used to measure the propagation of code between developers. We examine the effects of repository popularity on two aspects of knowledge transfer, innovation adoption and sociality, measured on a dataset of GitHub fork events.
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Notes
- 1.
Data was retrieved on Jan 16, 2018.
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Acknowledgements
This work was partially supported by grant FA8650-18-C-7823 from the Defense Advanced Research Projects Agency (DARPA). The views and opinions contained in this article are the authors and should not be construed as official or as reflecting the views of the University of Central Florida, DARPA, or the U.S. Department of Defense.
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Appendix
Appendix
Our code for generating the innovation network from GitHub events can be found at https://github.com/aalrubaye/GithubDataAnalysis. Here are the algorithms for initializing and updating the network.
Algorithm 1: Constructing the model connections (repo–actor, repo–repo, and actor–followers) based on the ground truth dataset GD that includes repositories with fork events R, actors A, and their follower set F
Algorithm 2: Model update procedure for introducing fork events that have occurred since the last time point PM
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Al-Rubaye, A., Sukthankar, G. (2020). A Popularity-Based Model of the Diffusion of Innovation on GitHub. In: Carmichael, T., Yang, Z. (eds) Proceedings of the 2018 Conference of the Computational Social Science Society of the Americas. CSSSA 2018. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-030-35902-7_11
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