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

TL;DR

The paper investigates how OSS team dynamics influence practitioners' project selection and how motivations modulate these preferences. Using a mixed-methods online survey (n=198), it identifies communication quality, responsiveness, and inclusive practices as the core signals driving join decisions, while diversity signals are less emphasized overall. Motivations such as learning, helping, networking, and reputation reshape the importance of these team-dynamics signals, suggesting the need for motivation-aware, human-centric OSS recommender systems. The work proposes human–AI co-maintenance and governance practices to enhance collaboration quality and contributor retention, with practical implications for designing future social-aware project recommendations.

Abstract

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.

Figures (1)

• Figure 1: Summary of Survey Questionnaire