"My GitHub Sponsors profile is live!" Investigating the Impact of Twitter/X Mentions on GitHub Sponsors

TL;DR

This study examines whether tweets linking to GitHub Sponsors profiles influence sponsorship and developer activity. It combines large-scale quantitative and qualitative analyses of over 11,000 tweets, plus a causal-inference component using propensity score matching to estimate the impact on sponsorship, finding an ATT of $1.22$ additional sponsors per treated developer. The results show that GitHub Sponsors enjoys high visibility on Twitter/X but generally receives fewer likes, shares, and replies than Patreon or Open Collective, while activity on the developer side tends to rise in the week of posting. The work underscores the practical value of integrating social-media promotion with sponsorship platforms to bolster OSS funding and sustainability, and it suggests directions for future cross-platform analyses and template-based promotion strategies.

Abstract

GitHub Sponsors was launched in 2019, enabling donations to open-source software developers to provide financial support, as per GitHub's slogan: "Invest in the projects you depend on". However, a 2022 study on GitHub Sponsors found that only two-fifths of developers who were seeking sponsorship received a donation. The study found that, other than internal actions (such as offering perks to sponsors), developers had advertised their GitHub Sponsors profiles on social media, such as Twitter (also known as X). Therefore, in this work, we investigate the impact of tweets that contain links to GitHub Sponsors profiles on sponsorship, as well as their reception on Twitter/X. We further characterize these tweets to understand their context and find that (1) such tweets have the impact of increasing the number of sponsors acquired, (2) compared to other donation platforms such as Open Collective and Patreon, GitHub Sponsors has significantly fewer interactions but is more visible on Twitter/X, and (3) developers tend to contribute more to open-source software during the week of posting such tweets. Our findings are the first step toward investigating the impact of social media on obtaining funding to sustain open-source software.

Figures (1)

• Figure 1: Covariate balance before (unadjusted) and after (adjusted) propensity score matching.