分析25年开源项目数据，揭示贡献者影响力背后的网络角色与动态规律。
Beyond Code Contributions: How Network Position, Temporal Bursts, and Code Review Activities Shape Contributor Influence in Large-Scale Open Source Ecosystems
- 基于图神经网络和时序分析，识别出五类贡献者角色及其结构作用。
- 顶层1%贡献者掌握大部分网络影响力，桥接者对网络稳定影响极大。
- 适合开源社区治理者、平台管理者及研究者参考，助力健康生态建设。
开源软件（OSS）项目依赖复杂的贡献者网络，其互动推动创新与可持续发展。本研究利用先进图神经网络与时序网络分析，基于云原生计算基金会生态系统25年数据（涵盖沙盒、孵化及毕业项目），分析数千名贡献者在数百个仓库中的行为。结果发现，贡献者影响力呈强幂律分布，前1%贡献者掌控显著份额。通过GPU加速的PageRank、介数中心性及自定义LSTM模型，识别出五类角色：核心、桥接、连接、常规与边缘，各自具有独特网络位置与结构重要性。统计分析显示，提交、拉取请求、问题创建等动作与影响力显著相关，多元回归模型解释了大量影响力方差。时序分析表明，网络密度、聚类系数与模块度存在显著时间趋势，重大里程碑处出现制度性变化。结构完整性模拟显示，桥接者虽占少数，但移除后对网络连通性影响巨大。研究为战略保留政策提供实证支持，并给出可操作的社区健康指标。
原文摘要 · Abstract (English)
Open source software (OSS) projects rely on complex networks of contributors whose interactions drive innovation and sustainability. This study presents a comprehensive analysis of OSS contributor networks using advanced graph neural networks and temporal network analysis on data spanning 25 years from the Cloud Native Computing Foundation ecosystem, encompassing sandbox, incubating, and graduated projects. Our analysis of thousands of contributors across hundreds of repositories reveals that OSS networks exhibit strong power-law distributions in influence, with the top 1\% of contributors controlling a substantial portion of network influence. Using GPU-accelerated PageRank, betweenness centrality, and custom LSTM models, we identify five distinct contributor roles: Core, Bridge, Connector, Regular, and Peripheral, each with unique network positions and structural importance. Statistical analysis reveals significant correlations between specific action types (commits, pull requests, issues) and contributor influence, with multiple regression models explaining substantial variance in influence metrics. Temporal analysis shows that network density, clustering coefficients, and modularity exhibit statistically significant temporal trends, with distinct regime changes coinciding with major project milestones. Structural integrity simulations show that Bridge contributors, despite representing a small fraction of the network, have a disproportionate impact on network cohesion when removed. Our findings provide empirical evidence for strategic contributor retention policies and offer actionable insights into community health metrics.
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