Attracting and retaining newcomers are critical for the sustainable development of Open Source Software (OSS) projects. Considerable efforts have been made to help newcomers identify and overcome barriers in the onboarding process. However, fewer studies focus on newcomers’ activities before their successful onboarding. Given the rising popularity of deep learning (DL) techniques, we wonder what the onboarding process of DL newcomers is, and if there exist commonalities or differences in the onboarding process for DL and non-DL newcomers. Therefore, we reported a study to understand the growth trends of DL and non-DL newcomers, mine DL and non-DL newcomers’ activities before their successful onboarding (i.e., past activities), and explore the relationships between newcomers’ past activities and their first commit patterns and retention rates. By analyzing 20 DL projects with 9,191 contributors and 20 non-DL projects with 9,839 contributors, and conducting email surveys with contributors, we derived the following findings: 1) DL projects have attracted and retained more newcomers than non-DL projects. 2) Compared to non-DL newcomers, DL newcomers encounter more deployment, documentation, and version issues before their successful onboarding. 3) DL newcomers statistically require more time to successfully onboard compared to non-DL newcomers, and DL newcomers with more past activities (e.g., issues, issue comments, and watch) are prone to submit an intensive first commit (i.e., a commit with many source code and documentation files being modified). Based on the findings, we shed light on the onboarding process for DL and non-DL newcomers, highlight future research directions, and provide practical suggestions to newcomers, researchers, and projects.

中文翻译：

---

了解深度学习项目中新人的入职流程

吸引和留住新人对于开源软件（OSS）项目的可持续发展至关重要。我们付出了大量努力来帮助新员工识别并克服入职过程中的障碍。然而，很少有研究关注新员工在成功入职之前的活动。鉴于深度学习 (DL) 技术的日益普及，我们想知道 DL 新手的入职流程是怎样的，以及 DL 和非 DL 新手的入职流程是否存在共性或差异。因此，我们报告了一项研究，旨在了解 DL 和非 DL 新人的增长趋势，挖掘 DL 和非 DL 新人在成功入职之前的活动（即过去的活动），并探讨新人过去的活动与他们的关系之间的关系。首次提交模式和保留率。通过分析 20 个拥有 9,191 名贡献者的深度学习项目和 20 个拥有 9,839 名贡献者的非深度学习项目，并对贡献者进行电子邮件调查，我们得出以下发现： 1）深度学习项目比非深度学习项目吸引和留住了更多新人。 2）与非深度学习新手相比，深度学习新手在成功入职之前会遇到更多部署、文档和版本问题。 3) 从统计数据来看，与非深度学习新手相比，深度学习新手需要更多时间才能成功加入，并且具有更多过去活动（例如问题、问题评论和观看）的深度学习新手倾向于提交密集的首次提交（即，提交许多源代码和文档文件正在修改）。根据调查结果，我们阐明了深度学习和非深度学习新人的入职流程，突出了未来的研究方向，并为新人、研究人员和项目提供了实用的建议。