Understanding the Factors that Impact the Popularity of GitHub Repositories (ICSME 2016)

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 could help them on building and evolving systems in a competitive software market.

Transcript

1. Understanding the Factors
   that Impact the Popularity of
   GitHub Repositories
   Hudson Borges, Andre Hora, Marco Tulio Valente
   {hsborges, hora, mtov}@dcc.ufmg.br
   

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2. Introduction
   15M users 36M repositories
   2
   

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3. Social Coding Features
   3
   “Stars are used to show appreciation to the repository maintainer for their work”
   

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4. “Our First 50,000 Stars”
   4
   https://facebook.github.io/react/blog/2016/09/28/our-first-50000-stars.html
   

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5. Our Goal
   ● Investigate the factors and the patterns that govern the
   popularity of GitHub repositories
   5
   Attractiveness Competitiveness
   

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6. Our work
   1. Quantitative Analysis
   2. Popularity growth patterns
   3. Qualitative Study with Developers
   6
   

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7. Data Collection
   ● March, 2016
   ● Top-2,500 repositories
   ○ Stars, creation date, language, etc.
   ● Historical data on # stars
   ● Six application domains
   ○ Manual classification
   ○ https://goo.gl/73Sbvz
   7
   Official GitHub API
   

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8. ( Some ) Results
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9. 9
   Different distributions
   by applying
   Kruskal-Wallis
   Programming Language
   … 50+ different languages
   

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10. 10
    Different distributions
    by applying
    Kruskal-Wallis
    Application Domain
    

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11. 11
    Different distributions
    by applying
    Mann-Whitney
    Repository Owner
    

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12. Correlation Analysis
    12
    Age
    No correlation
    Contributors
    Weak correlation
    Commits
    Weak correlation
    Forks
    Strong correlation
    

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13. Popularity Growth Patterns
    ● K-Spectral Centroid clustering algorithm
    ○ Clusters time series with similar shapes
    ○ Invariant to scaling and shifting
    13
    

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14. 14
    Popularity Growth Patterns
    Slow Moderate
    Fast Viral
    

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15. Growth Patterns x Language
    15
    92.6%
    4.5%
    1.1%
    1.6%
    38.7%
    51.9%
    7.6%
    1.6%
    Slow
    Moderate
    Fast
    Viral
    

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16. Growth Patterns x Domain
    16
    75.5%
    18.2%
    4.9%
    1.2%
    51.9%
    33.5%
    9.8%
    4.6%
    Slow
    Moderate
    Fast
    Viral
    

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17. Developers Feedback
    A. Impact of account types (users vs organizations)
    B. Features implemented in successful releases
    C. Reasons for viral growth
    17
    

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18. Repositories owned by organizations are more popular than
    the ones owned by individuals (RQ #1)
    Repositories Owned by Users
    18
    Top-100
    Repositories
    30
    Users
    17
    Public emails
    5
    Responses
    

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19. 1. Do you plan to migrate to an organization account?
    ➢ All developers answered negatively
    19
    Repositories Owned by Users
    “I worked hard to create the project, and having it
    under my personal username is necessary to
    have proper credit for it.”
    

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20. Successful Releases
    20
    60
    Releases with highest
    impact
    25
    Responses
    How the features were
    selected?
    

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21. Reasons for Viral Growth
    21
    22
    Viral growth
    14
    Responses
    How do you explain the peaks
    in the number of stars?
    

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22. Reasons for Viral Growth
    22
    22
    Viral growth
    14
    Responses
    “I posted about this project on
    HackerNews. It quickly got a lot of
    attention and remained on the front page
    of HackerNews for over 24 hours ...”
    How do you explain the peaks
    in the number of stars?
    

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23. Conclusion
    ➢ Domains/languages/owners may impact popularity
    ➢ Strong correlation between popularity and forks
    ➢ Repositories receive more stars right after creation
    and after releases
    Factors and Properties
    23
    

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24. Conclusion
    ➢ Slow, Moderate, Fast, and Viral
    ➢ Slow is the most common pattern
    ➢ Viral is the less common pattern
    Popularity Growth Patterns
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25. Conclusion
    ➢ Developers look for recognition
    ➢ Popular features are identified by developers
    themselves
    ➢ Peaks of popularity are triggered by social
    media posts
    Qualitative study
    25
    

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26. Future Work
    ➢ Popular vs unpopular repositories
    ➢ Causality analysis
    ➢ Popularity prediction
    26
    

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27. Tool Support
    http://gittrends.io
    27
    

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28. Thank you!
    28
    

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