Coding together – coding alone: the role of trust in collaborative programming

Abstract

In the digital economy, innovation processes increasingly rely on highly specialised know-how and open-source software shared on digital platforms on collaborative programming. The information that feeds into the content on these platforms is provided voluntarily by a vast crowd of knowledgeable users from all over the world. In contributing to the platforms, users invest their time and share knowledge with strangers to add to the rising body of digital knowledge.This requires an open mindset and trust. In this study, we argue that such a mindset is not just an individual asset, but determined by the local communities the users are embedded in. We, therefore, hypothesise that places with higher levels of trust should contribute more to Stack Overflow, the world's largest question-and-answer platform for programming questions. In relating the city-level contributions of 266 OECD metropolitan areas to infrastructure, economic, and trust measures, we find this hypothesis confirmed. In contrast, click rates to the platform are solely driven by infrastructure and economic variables, but not by trust. These findings highlight the importance of societal values in the 21st century knowledge economy: if policymakers want to develop a lively local digital economy, it is not enough to provide fast Internet access and business opportunities. Instead, it is equally important to establish a trust-building environment that fosters sharing of innovative ideas, collaborations, and knowledge spillovers. J 24, L 17, O 35, R 12 JEL CLASSIFICATION

Trouble in programmer's paradise: gender-biases in sharing and recognising technical knowledge on Stack Overflow

“…A focus on the Anglosphere means that I limit the study to a Western and white conception of gender. Previous work in this field has shown that user location can be a significant mediator of how contributions on SO are evaluated (Stephany et al, 2020). I am not able to foreground intersectionality in this work, with ethnicity largely obscured in the data.…”

“…In turning to existing scholarship on SO, the role of gender in metrics of success and activity has been analysed on an individual level (Ford et al, 2016;May et al, 2019;Vasilescu et al, 2012), however the effect of gender on interaction dynamics and evaluation of contributions has yet to be studied. Scholars have employed social network analysis to examine geographies of participation on SO (Stephany et al, 2020), but not gender. I therefore aim to shed new light on how gender-biases dictate the recognition and sharing of technical knowledge.…”