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

TL;DR

This paper explores how team dynamics and contributor motivations influence OSS project selection, revealing that communication quality and community inclusiveness are key factors affecting contributor decisions and suggesting improvements for recommendation systems.

Contribution

It provides empirical insights into the role of team dynamics and motivation in OSS project selection, informing the design of human-aware recommendation systems.

Findings

Communication dynamics like responsiveness and tone are highly valued.

Motivations such as reputation and networking influence preferences for inclusive communities.

Understanding these factors can improve OSS project recommendation accuracy.

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.