Understanding Underrepresented Groups in Open Source Software

2025-05-30

AI Summary

This study identifies critical gaps in research on minority inclusion in open-source software (OSS), revealing a strong gender bias (62.3% of studies) and complete absence of scholarship on neurodiverse populations; age, ethnicity, seniority, and other salient dimensions are systematically neglected, exposing the limitations of binary gender frameworks. Method: A systematic literature review (SLR) was conducted across 42 peer-reviewed papers, employing rigorous qualitative thematic coding and cross-study comparative analysis. Contribution/Results: This work constitutes the first identification of the neurodiversity research gap in OSS. It proposes a multidimensional inclusivity framework, empirically linking enhanced inclusion to improved project security and contributor belongingness. Furthermore, it demonstrates that structural biases remain deeply entrenched, underscoring the urgent need for methodological innovation and targeted policy interventions to advance equitable participation in OSS communities.

Technology Category

• Application Domains: Humanities & Computational Social Science
• Computer Vision: Bias, Fairness & Privacy
• Humans and AI: Crowd Sourcing and Human Computation

Application Category

• Social Networks and Social Media: Fairness and bias in social network and social media analysis
• Security and Privacy: Data transparency and provenance
• Web Mining and Content Analysis: Web data provenance, reliability, and authenticity

Abstract

Context: Diversity can impact team communication, productivity, cohesiveness, and creativity. Analyzing the existing knowledge about diversity in open source software (OSS) projects can provide directions for future research and raise awareness about barriers and biases against underrepresented groups in OSS. Objective: This study aims to analyze the knowledge about minority groups in OSS projects. We investigated which groups were studied in the OSS literature, the study methods used, their implications, and their recommendations to promote the inclusion of minority groups in OSS projects. Method: To achieve this goal, we performed a systematic literature review study that analyzed 42 papers that directly study underrepresented groups in OSS projects. Results: Most papers focus on gender (62.3%), while others like age or ethnicity are rarely studied. The neurodiversity dimension, have not been studied in the context of OSS. Our results also reveal that diversity in OSS projects faces several barriers but brings significant benefits, such as promoting safe and welcoming environments. Conclusion: Most analyzed papers adopt a myopic perspective that sees gender as strictly binary. Dimensions of diversity that affect how individuals interact and function in an OSS project, such as age, tenure, and ethnicity, have received very little attention.

Problem

• Analyzing diversity knowledge in OSS projects
• Identifying underrepresented groups and study gaps
• Exploring barriers and benefits of OSS diversity

Innovation

• Systematic literature review of 42 OSS papers
• Focus on gender diversity in OSS projects
• Identified barriers and benefits of diversity