Studying donations and their expenses in open source projects: a case study of GitHub projects collecting donations through open collectives

Zhou, Jiayuan; Kamei, Yasutaka; Hassan, Ahmed E.; Ubayashi, Naoyasu

doi:10.1007/s10664-021-10060-y

Cited by 4 publications

(2 citation statements)

References 29 publications

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“…Recently, Zhou et al [49] explored donations on the Open Collective platform that support open-source projects. They indicated the influence of individual donors; although corporate donors tend to donate more money than individual donors for an individual donation, the total donation amount from individual donors is greater than corporate donors.…”

Section: Related Workmentioning

confidence: 99%

“…Open-source software (OSS) is ubiquitous, but sustaining it is a challenge [28]. Maintaining an OSS project requires not only intrinsic motivation (e.g., joy of participation) but also extrinsic motivation (e.g., financial incentives) [49]. The last few years have seen the emergence of many platforms that allow open-source developers to receive donations for their work, such as PayPal [30], Open Collective [11], Patreon [29], and GitHub Sponsors [37].…”

Section: Introductionmentioning

confidence: 99%

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

Fan,

Xiao,

Hata

et al. 2024

Proceedings of the IEEE/ACM 46th International Conference on Software Engineering

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GitHub Sponsors was launched in 2019, enabling donations to opensource 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. CCS CONCEPTS• Social and professional topics → Sustainability; • Software and its engineering → Open source model.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Fan,

Xiao,

Hata

et al. 2024

Proceedings of the IEEE/ACM 46th International Conference on Software Engineering

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An Empirical Study on GitHub Sponsor Mechanism

Zhang¹,

Yang²,

He³

et al. 2023

Int. J. Soft. Eng. Knowl. Eng.

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From May 2019, GitHub launched sponsor mechanism indicating that GitHub is moving towards deeper integration of open source development and economic support. It will bring more comprehensive and diversified support to the open source community. However, the number of developers profiting from the sponsor mechanism follows a long tail distribution. Our study found that only 31% of developers who started the sponsor mechanism received rewards, and 39.3% of them only received a reward of one dollar. Our work focuses on identifying what factors affect the availability of sponsorship for developers in open source community. We start by defining 45 features to characterize the developers in four dimensions i.e. Personality, Advertisement, Repository and Behavior. The results of statistical analysis indicate that most of the proposed features differ significantly between the ones who received rewards (short for MTs_Yes) from those that are not. After that, we build machine learning model based on the proposed features to predict MTs_Yes. Compared with the existing work, results show that our method outperforms baselines by 30% for AUC (Area Under the Curve). In addition, we investigated the relative contribution of features in detecting MTs_Yes and analyzed the important features by using an interpretable model SHAP. Finally, based on the experimental results, we put forward corresponding and practical suggestions for developers who want to receive rewards so as to make the community of open source projects develop more harmonious.

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How to characterize the health of an Open Source Software project? A snowball literature review of an emerging practice

Linåker

Papatheocharous

Olsson

2022

Proceedings of the 18th International Symposium on Open Collaboration

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Studying donations and their expenses in open source projects: a case study of GitHub projects collecting donations through open collectives

Cited by 4 publications

References 29 publications

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

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

An Empirical Study on GitHub Sponsor Mechanism

How to characterize the health of an Open Source Software project? A snowball literature review of an emerging practice

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