Understanding the Factors that Impact the Popularity of GitHub Repositories (1606.04984v3)

Abstract: Software popularity is a valuable information to modern open source developers, who constantly want to know if their systems are attracting new users, if new releases are gaining acceptance, or if they are meeting user's expectations. In this paper, we describe a study on the popularity of software systems hosted at GitHub, which is the world's largest collection of open source software. GitHub provides an explicit way for users to manifest their satisfaction with a hosted repository: the stargazers button. In our study, we reveal the main factors that impact the number of stars of GitHub projects, including programming language and application domain. We also study the impact of new features on project popularity. Finally, we identify four main patterns of popularity growth, which are derived after clustering the time series representing the number of stars of 2,279 popular GitHub repositories. We hope our results provide valuable insights to developers and maintainers, which can help them on building and evolving systems in a competitive software market.

• The paper reveals that programming language and application domain significantly influence repository popularity.
• It employs cluster analysis on time series data to show a strong correlation between the number of forks and star counts.
• The study finds that repositories garner most stars shortly after release, highlighting the impact of initial adoption and key releases.

Understanding the Factors that Impact the Popularity of GitHub Repositories

The paper "Understanding the Factors that Impact the Popularity of GitHub Repositories" offers a comprehensive analysis of the factors influencing the popularity of software projects on GitHub. Authors Hudson Borges, Andre Hora, and Marco Tulio Valente focus on quantifying software popularity using GitHub stars as an indicator, exploring variables such as programming language, application domain, and project characteristics. This paper leverages a dataset of the top-2,500 most starred public repositories on GitHub to examine these factors through a series of formulated research questions.

Methodology

The authors employ a variety of analytical techniques, including cluster analysis on time series data, to derive insights into growth patterns of repository popularity over time. They utilize GitHub API data to assemble a comprehensive dataset, which offers a historical depiction of project's star counts. Four research questions guide the analysis, examining the correlation between popularity and variables such as programming language, age, number of forks, and more.

Key Findings

1. Programming Language and Application Domain: JavaScript is noted as the most popular programming language, both in terms of the number of repositories and median star count. Furthermore, the application domain significantly impacts popularity, with systems software and web libraries showing the highest median star counts.
2. Characteristics Impacting Popularity: While correlation with factors such as number of commits and contributors is weak, a strong correlation was found between popularity and the number of forks. This indicates projects with higher collaboration potential tend to be more popular.
3. Popularity Growth: The research identifies that projects typically receive a significant number of stars shortly after release. This growth is more concentrated during early life stages of repositories, indicating a strong initial adoption phase.
4. Release Impact: The analysis indicates an uptick in star counts following project releases, particularly significant feature releases. However, the effect size varies, and while not all projects experience substantial growth post-release, it still plays a non-negligible role.
5. Growth Patterns: Four primary patterns of popularity growth were identified – Slow, Moderate, Fast, and Viral Growth. Slow growth is the most prevalent, encompassing majority of the repositories, but Viral Growth patterns, although rare, indicate sharp increases in popularity often due to external factors, such as social media exposure.

Practical and Theoretical Implications

From a practical standpoint, this paper provides actionable insights for developers and maintainers looking to increase their project's visibility and attractiveness. Understanding the aspects that correlate with popularity can guide strategic decisions, such as employing certain programming languages or targeting specific application domains. Theoretically, this paper enriches the literature on open-source software popularity by providing a structured approach to analyzing project visibility factors, paralleling studies in social media and digital content engagement.

Future Directions

The authors suggest expanding the research to include less popular repositories for comparison, studying popularity within specific communities and languages, and developing predictive models that alert developers to potential stagnation. These future directions could significantly enhance our understanding of software ecosystems on collaborative platforms like GitHub.

In summary, this paper contributes significant empirical findings to the discourse on software repository popularity, with implications for both practitioners seeking to elevate their GitHub projects and researchers aiming to explore the mechanics of digital popularity and collaboration.