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Influence analysis of Github repositories.

Yan Hu1, Jun Zhang1, Xiaomei Bai1

  • 1School of Software, Dalian University of Technology, Development Zone, Dalian, 116620 China.

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|August 20, 2016
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Summary
This summary is machine-generated.

This study introduces a weighted HITS algorithm to analyze GitHub repository influence. It reveals distinct influential repositories compared to standard methods, offering new insights into software engineering dynamics.

Keywords:
GithubHITSInfluence analysisSocial coding

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Area of Science:

  • Computer Science
  • Software Engineering
  • Data Mining

Background:

  • Social coding platforms like GitHub have transformed software development.
  • GitHub's growth presents challenges in understanding repository importance.
  • Analyzing influence is crucial for navigating large-scale software ecosystems.

Purpose of the Study:

  • To develop a method for analyzing the importance and influence of GitHub repositories.
  • To adapt graph-based influence analysis techniques for social coding platforms.
  • To investigate repository influence over time using monthly data.

Main Methods:

  • Proposed a HITS (Hyperlink-Induced Topic Search) based influence analysis.
  • Constructed graphs representing the star relationships between GitHub users and repositories.
  • Applied a weighted version of the HITS algorithm to the star graph.
  • Conducted influence analysis on per-month star graphs to track dynamic rankings.

Main Results:

  • The weighted HITS algorithm identified a different set of top influential repositories compared to the standard HITS.
  • Analysis of per-month star graphs revealed monthly variations in repository influence rankings.
  • The study provides a novel approach to quantify repository impact within the GitHub ecosystem.

Conclusions:

  • Influence analysis on GitHub repositories is essential for software engineering research.
  • Weighted HITS offers a more nuanced understanding of repository importance than standard algorithms.
  • Dynamic analysis of influence over time provides valuable insights into evolving software trends.