Identifying Developer Engagement in Open-Source Software Blockchain Projects through Factor Analysis
Location
Online
Event Website
https://hicss.hawaii.edu/
Start Date
3-1-2023 12:00 AM
End Date
7-1-2023 12:00 AM
Description
The ubiquity of GitHub for software developers to coordinate software development in a community platform has resulted in a rich source of public data. Blockchain teams put open-source code as a founding principle since the release of Bitcoin and nearly all blockchain-based projects have code visible on GitHub. Developer engagement is known to be important to the health and viability of open-source software, yet has varying definitions and no standard method of measuring what constitutes engagement. This work uses exploratory factor analysis to identify dimensions that represent engagement in a community of open-source developers. We find that a latent factor composed of pull-requests, commits, comments, and authors based on a monthly average of the previous three months is a representation of Developer Engagement. A secondary factor consists of stars, forks, and total authors. Cross validation of the dataset is carried out with good support for the model.
Recommended Citation
Nijsse, Jeff and Litchfield, Alan, "Identifying Developer Engagement in Open-Source Software Blockchain Projects through Factor Analysis" (2023). Hawaii International Conference on System Sciences 2023 (HICSS-56). 5.
https://aisel.aisnet.org/hicss-56/os/blockchain/5
Identifying Developer Engagement in Open-Source Software Blockchain Projects through Factor Analysis
Online
The ubiquity of GitHub for software developers to coordinate software development in a community platform has resulted in a rich source of public data. Blockchain teams put open-source code as a founding principle since the release of Bitcoin and nearly all blockchain-based projects have code visible on GitHub. Developer engagement is known to be important to the health and viability of open-source software, yet has varying definitions and no standard method of measuring what constitutes engagement. This work uses exploratory factor analysis to identify dimensions that represent engagement in a community of open-source developers. We find that a latent factor composed of pull-requests, commits, comments, and authors based on a monthly average of the previous three months is a representation of Developer Engagement. A secondary factor consists of stars, forks, and total authors. Cross validation of the dataset is carried out with good support for the model.
https://aisel.aisnet.org/hicss-56/os/blockchain/5