arXivDaily arXiv每日学术速递 周一至周五更新
arXiv周末暂无论文更新,休息一下吧,周末愉快~~
arXiv 2602.11692cs.SE
收藏

超越代码:团队动态如何影响OSS项目选择的实证洞察

Beyond Code: Empirical Insights into How Team Dynamics Influence OSS Project Selection

Deakin University(迪肯大学);RMIT University(皇家墨尔本理工大学)

Shashiwadana Nirmani, Hourieh Khalajzadeh, Mojtaba Shahin, Xiao Liu

AI总结:

本研究通过实证分析揭示团队动态与贡献者动机之间的关系,为设计更符合社交协作质量的OSS项目推荐系统提供依据。

摘要:

开源软件(OSS)开发依赖于分布式贡献者之间的有效协作。然而,当前的OSS项目推荐系统主要强调技术属性,忽视了影响贡献者加入和留在项目中的协作和社区因素。本研究探讨了OSS社区内部的团队动态如何影响项目选择,以及这些偏好如何因贡献者的动机而异。我们通过在线调查收集了198名OSS从业者的数据,结合定量和定性分析来捕捉贡献者对团队动态的看法。结果发现,与沟通相关的团队动态,如响应性、语气和回复的清晰度,在从业者中始终被优先考虑。然而,这些团队动态的相对重要性会因贡献者的动机而不同。例如,受声誉或社交网络动机驱动的从业者更倾向于包容性的项目社区,这些社区鼓励多样化的参与。这些发现强调,理解团队动态如何与贡献者的动机相匹配,为从业者项目选择行为提供了有价值的洞察。这些洞察可以指导未来的人工智能项目推荐系统的设计,使其更好地考虑社交协作质量和动机契合度。

英文摘要:

Open-source software (OSS) development relies on effective collaboration among distributed contributors. Yet, current OSS project recommendation systems primarily emphasize technical attributes, overlooking the collaboration and community aspects that influence contributors' decisions to join and remain in projects. This study investigates how team dynamics within OSS communities influence project selection and how these preferences vary across contributors' motivations. We conducted an online survey with 198 OSS practitioners, combining quantitative and qualitative analyses to capture contributors' perceptions of team dynamics. The results reveal that communication-related team dynamics such as responsiveness, tone, and clarity of replies are consistently prioritized across practitioners. However, the relative importance of these team dynamics differs according to contributors' motivations. For instance, practitioners motivated by gaining reputation or networking preferred inclusive project communities that encouraged diverse participation. These findings highlight that understanding how team dynamics align with contributors' motivations provides valuable insights into practitioners' project selection behaviour. Those insights can inform the design of future human-aware project recommendation systems that better account for social collaboration quality and motivational fit.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑