Open-source software (OSS) development platforms, such as GitHub, expand the potential for cross-national collaboration among developers by lowering the geographic, temporal, and coordination barriers that limited software innovation in the past. However, research has shown that the technological affordances that facilitate cross-national collaboration do not uniformly benefit all countries. Using the GitHub Innovation Graph dataset, which aggregates the complete cross-country collaborations among the entire population of GitHub developers, we present quantitative evidence of deep-seated religious and cultural affinities, shared colonial histories, and geopolitical factors structuring the collaborations between non-U.S. country pairs that become visible when the overarching dominance of the U.S. is removed from the data. This study highlights the opportunities to develop decentralizing strategies to facilitate new collaborations between developers in non-U.S. countries, thereby fostering the development of novel, innovative solutions. More generally, this study also underscores the importance of contextualizing user behavior and knowledge management in information systems with long-term, macro-social conditions in which these systems are inextricably embedded.

Who creates the most innovative open-source software projects? And what fate do these projects tend to have? Building on a long history of research to understand innovation in business and other domains, as well as recent advances towards modeling innovation in scientific research from the science of science field, in this paper we adopt the analogy of innovation as emerging from the novel recombination of existing bits of knowledge. As such, we consider as innovative the software projects that recombine existing software libraries in novel ways, i.e., those built on top of atypical combinations of packages as extracted from import statements. We then report on a large-scale quantitative study of innovation in the Python open-source software ecosystem. Our results show that higher levels of innovativeness are statistically associated with higher GitHub star counts, i.e., novelty begets popularity. At the same time, we find that controlling for project size, the more innovative projects tend to involve smaller teams of contributors, as well as be at higher risk of becoming abandoned in the long term. We conclude that innovation and open source sustainability are closely related and, to some extent, antagonistic.

The diffusion of information about open-source projects is a key factor influencing the adoption of projects and the allocation of developer efforts. Developers learn about new projects, and evaluate their quality and importance by accessing the related information. Social media is an important channel for information diffusion about open-source projects, with previous research suggesting the existence of a social media ecosystem that consists of multiple platforms and collectively supports information diffusion in open source.With different features supporting information diffusion, the same piece of information likely reaches different developer communities on different platforms, which attracts the attention and contribution of different developers and thus influences the success of open-source projects. Despite its importance, few works looked at the identity of the developer community that project-related information reaches on social media platforms and its associated impact on the discussed project.In this work, we track social media discussions on open-source projects on three different platforms: Twitter, HackerNews, and Reddit. We first describe the dynamics of project-related information diffusion across platforms, and we analyze the association between the number of posts on each platform, and the number of developers attracted to the discussed project from different communities. We find that posts about open-source projects first appear on Twitter and HackerNews, then move more towards Reddit. The number of project-related posts on Twitter mostly associate with the attracted developers from communities that are close to the project’s main contributor, while posts on other platforms associate more with the attention from remote communities.

Attracting and retaining new developers is often at the heart of open-source project sustainability and success. Previous research found many intrinsic (or endogenous) project characteristics associated with the attractiveness of projects to new developers, but the impact of factors external to the project itself have largely been overlooked. In this work, we focus on one such external factor, a project's labor pool, which is defined as the set of contributors active in the overall open-source ecosystem that the project could plausibly attempt to recruit from at a given time. How are the size and characteristics of the labor pool associated with a project's attractiveness to new contributors? Through an empirical study of over 516,893 Python projects, we found that the size of the project's labor pool, the technical skill match, and the social connection between the project's labor pool and members of the focal project all significantly influence the number of new developers that the focal project attracts, with the competition between projects with overlapping labor pools also playing a role. Overall, the labor pool factors add considerable explanatory power compared to models with only project-level characteristics.

Twitter is widely used by software developers. But how effective are tweets at promoting open source projects? How could one use Twitter to increase a project's popularity or attract new contributors? In this paper we report on a mixed-methods empirical study of 44,544 tweets containing links to 2,370 open-source GitHub repositories, looking for evidence of causal effects of these tweets on the projects attracting new GitHub stars and contributors, as well as characterizing the high-impact tweets, the people likely being attracted by them, and how they differ from contributors attracted otherwise. Among others, we find that tweets have a statistically significant and practically sizable effect on obtaining new stars and a small average effect on attracting new contributors. The popularity, content of the tweet, as well as the identity of tweet authors all affect the scale of the attraction effect. In addition, our qualitative analysis suggests that forming an active Twitter community for an open source project plays an important role in attracting new committers via tweets. We also report that developers who are new to GitHub or have a long history of Twitter usage but few tweets posted are most likely to be attracted as contributors to the repositories mentioned by tweets. Our work contributes to the literature on open source sustainability.

Social media, especially Twitter, has always been a part of the professional lives of software developers, with prior work reporting on a diversity of usage scenarios, including sharing information, staying current, and promoting one's work. However, previous studies of Twitter use by software developers typically lack information about activities of the study subjects (and their outcomes) on other platforms. To enable such future research, in this paper we propose a computational approach to cross-link users across Twitter and GitHub, revealing (at least) 70,427 users active on both. As a preliminary analysis of this dataset, we report on a case study of 786 tweets by open-source developers about GitHub work, combining automatic characterization of tweet authors in terms of their relationship to the GitHub items linked in their tweets with qualitative analysis of the tweet contents. We find that different developer roles tend to have different tweeting behaviors, with repository owners being perhaps the most distinctive group compared to other project contributors and followers. We also note a sizeable group of people who follow others on GitHub and tweet about these people's work, but do not otherwise contribute to those open-source projects. Our results and public dataset open up multiple future research directions.