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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. 

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 asso- ciated 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 dened 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 be- tween the project’s labor pool and members of the focal project all signicantly inuence 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. 

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 projectrelated 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. 

While the severe underrepresentation of women and non-binary people in open source is widely recognized, there is little empirical data on how the situation has changed over time and which subcommunities have been more effectively reducing the gender imbalance. To obtain a clearer image of gender representation in open source, we compiled and synthesized existing empirical data from the literature, and computed historical trends in the representation of women across 20 open source ecosystems. While inherently limited by the ability of automatic name-based gender inference to capture true gender identities at an individual level, our census still provides valuable population-level insights. Across all and in most ecosystems, we observed a promising upward trend in the percentage of women among code contributors over time, but also high variation in the percentage of women contributors across ecosystems. We also found that, in most ecosystems, women withdraw earlier from open-source participation than men. 

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.