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arxiv: 1907.04002 · v1 · pith:YFM2ICP3new · submitted 2019-07-09 · 💻 cs.CY · cs.CR

Characterizing Bitcoin donations to open source software on GitHub

Pith reviewed 2026-05-25 00:18 UTC · model grok-4.3

classification 💻 cs.CY cs.CR
keywords bitcoingithubopen sourcedonationsblockchaincryptocurrencyrepository analysissoftware funding
0
0 comments X

The pith

Bitcoin donations to GitHub open source repositories total only 8.3 million dollars over ten years.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper measures Bitcoin's role as a donation channel for open source projects on GitHub by scanning millions of repositories for addresses and tracing the linked blockchain activity. It reports low overall usage, with roughly 44 thousand deposits amounting to 8.3 million dollars across a decade. The analysis also tests whether donation volume tracks repository age or popularity indicators such as stars, forks, and watchers. Only weak positive correlations appear, the strongest being r=0.013 with the number of forks.

Core claim

We scanned over three million repositories looking for donation addresses. We then extracted and analyzed their transactions from Bitcoin's public blockchain. Overall, we found a limited adoption of Bitcoin as a payment method for receiving donations, with nearly 44 thousand deposits adding up to only 8.3 million dollars in the last 10 years. We also found weak positive correlation between the amount of donations in dollars and the popularity of a repository, with highest correlation (r=0.013) associated with number of forks.

What carries the argument

Identification of Bitcoin addresses embedded in repository files or descriptions, followed by extraction of their on-chain transaction histories.

If this is right

  • Bitcoin functions as a minor donation method for open source projects hosted on GitHub.
  • Total recorded donations stay small at 8.3 million dollars across ten years.
  • Donation amounts display only weak positive links to measures of repository popularity.
  • The number of forks exhibits the strongest (yet still modest) association with donation size among the popularity metrics examined.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Projects seeking larger donations may need to combine Bitcoin with other payment rails or funding models.
  • The low totals could reflect broader donor preferences for non-cryptocurrency channels when supporting open source work.
  • Future scans that also capture addresses for other cryptocurrencies would allow direct comparison of adoption rates.

Load-bearing premise

Addresses found in repository files or descriptions are mainly donation addresses rather than addresses used for other purposes.

What would settle it

A manual audit of a representative sample of repositories that shows most extracted addresses receive no donations or that aggregate volumes greatly exceed 8.3 million dollars.

Figures

Figures reproduced from arXiv: 1907.04002 by Husam Al Jawaheri, Mashael Al Sabah, Yazan Boshmaf, Yury Zhauniarovich.

Figure 1
Figure 1. Figure 1: Repository information on GitHub. projects into code repositories, which enables them to display, re￾view, search, and navigate through their source code. Moreover, the service provides issue tracking, project planning, documentation, and release management tools. There is also a social networking feature that allows developers to watch, star, and fork repositories. As such, these social interactions can b… view at source ↗
Figure 2
Figure 2. Figure 2: Total amount of donations vs. exchange rate. [PITH_FULL_IMAGE:figures/full_fig_p005_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Monthly amount of donations. with their bitcoins, and the total amount of donations has plum￾meted to a few thousand dollars a month, without large deposits. 4.3 Popularity and age As shown in §4.2, some of the addresses that received large amounts of donations were listed in relatively new, unpopular repositories. Our goal is to further explore this relationship and analyze how repository information, its… view at source ↗
Figure 4
Figure 4. Figure 4: Correlation between repository information and donations. [PITH_FULL_IMAGE:figures/full_fig_p006_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: Correlation matrix of repository information. [PITH_FULL_IMAGE:figures/full_fig_p006_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Correlation matrix of address information. [PITH_FULL_IMAGE:figures/full_fig_p007_6.png] view at source ↗
read the original abstract

Web-based hosting services for version control, such as GitHub, have made it easier for people to develop, share, and donate money to software repositories. In this paper, we study the use of Bitcoin to make donations to open source repositories on GitHub. In particular, we analyze the amount and volume of donations over time, in addition to its relationship to the age and popularity of a repository. We scanned over three million repositories looking for donation addresses. We then extracted and analyzed their transactions from Bitcoin's public blockchain. Overall, we found a limited adoption of Bitcoin as a payment method for receiving donations, with nearly 44 thousand deposits adding up to only 8.3 million dollars in the last 10 years. We also found weak positive correlation between the amount of donations in dollars and the popularity of a repository, with highest correlation (r=0.013) associated with number of forks.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The paper scans over three million GitHub repositories for Bitcoin addresses appearing in files or descriptions, extracts the associated on-chain transactions, and reports limited adoption of Bitcoin donations (44k deposits totaling $8.3M over 10 years) together with weak positive correlations between donation volume in USD and repository popularity metrics (maximum r=0.013 for number of forks).

Significance. If the address-identification step is shown to be reliable, the work supplies the first large-scale empirical measurement of cryptocurrency donations to OSS projects, documenting both the modest aggregate volume and the near-absence of correlation with conventional popularity signals.

major comments (2)
  1. [Abstract] Abstract and implied Methods section: the headline figures (44k deposits, $8.3M total) and the subsequent correlation analysis rest entirely on the unvalidated assumption that every Bitcoin address string discovered by regex scanning is a donation address; no manual audit, precision estimate, or exclusion criteria for false positives (code examples, test vectors, copied addresses in dependencies) are described.
  2. [Abstract] Abstract: the reported correlation r=0.013 is presented as the strongest observed link, yet the manuscript supplies neither the exact sample size per metric, the p-values, nor any robustness check against contamination by non-donation addresses; if even a modest fraction of the 44k deposits are spurious, both the volume totals and the per-repository donation amounts used for the correlation become unreliable.
minor comments (2)
  1. Clarify the exact time window and exchange-rate source used to convert BTC to USD for the $8.3M aggregate.
  2. The phrase 'nearly 44 thousand deposits' should be accompanied by the precise count and the number of unique addresses.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive comments, which highlight important aspects of the address identification and statistical reporting. We address each point below and will incorporate revisions to improve clarity and rigor.

read point-by-point responses
  1. Referee: [Abstract] Abstract and implied Methods section: the headline figures (44k deposits, $8.3M total) and the subsequent correlation analysis rest entirely on the unvalidated assumption that every Bitcoin address string discovered by regex scanning is a donation address; no manual audit, precision estimate, or exclusion criteria for false positives (code examples, test vectors, copied addresses in dependencies) are described.

    Authors: We agree that the original manuscript would be strengthened by an explicit discussion of the address-scanning procedure and its limitations. The method relies on regex patterns matching the standard Bitcoin address format (base58check), followed by on-chain transaction extraction, but no manual audit or precision estimate was included. In revision we will add a dedicated methods subsection describing the regex, provide a small-scale manual validation on a random sample of detected addresses to estimate the false-positive rate, and discuss common sources of non-donation strings together with any exclusion rules applied. revision: yes

  2. Referee: [Abstract] Abstract: the reported correlation r=0.013 is presented as the strongest observed link, yet the manuscript supplies neither the exact sample size per metric, the p-values, nor any robustness check against contamination by non-donation addresses; if even a modest fraction of the 44k deposits are spurious, both the volume totals and the per-repository donation amounts used for the correlation become unreliable.

    Authors: The correlations were computed over the repositories that yielded at least one identified address and associated on-chain volume. We will revise the results section to report the precise sample size for each popularity metric, include the corresponding p-values, and add a sensitivity analysis that recomputes the correlations after randomly removing varying fractions of addresses to simulate possible contamination. This will directly address concerns about the reliability of the reported r values. revision: yes

Circularity Check

0 steps flagged

Empirical measurement study with no derivations or self-referential steps

full rationale

The paper performs a direct scan of >3M GitHub repositories for Bitcoin address strings, followed by extraction of on-chain transactions from the public blockchain. No equations, fitted parameters, predictions, or uniqueness theorems are present. Results (44k deposits, $8.3M total, r=0.013 correlation) are raw aggregates and statistical correlations computed from the collected data; they do not reduce to any input by construction. No self-citations are load-bearing for the central claims.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

The central claim depends on the domain assumption that identified addresses function as donations and that the repository scan is sufficiently complete to support statements about overall adoption.

axioms (2)
  • domain assumption Bitcoin addresses listed in repositories are donation addresses
    Core to identifying the 44k deposits; invoked when scanning repositories for addresses.
  • domain assumption The scan of three million repositories is representative of donation activity
    Required to generalize limited adoption from the sampled set.

pith-pipeline@v0.9.0 · 5696 in / 1267 out tokens · 29733 ms · 2026-05-25T00:18:48.749213+00:00 · methodology

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Lean theorems connected to this paper

Citations machine-checked in the Pith Canon. Every link opens the source theorem in the public Lean library.

  • IndisputableMonolith/Foundation/RealityFromDistinction.lean reality_from_one_distinction unclear
    ?
    unclear

    Relation between the paper passage and the cited Recognition theorem.

    We scanned over three million repositories looking for donation addresses. We then extracted and analyzed their transactions from Bitcoin's public blockchain. Overall, we found a limited adoption of Bitcoin as a payment method for receiving donations, with nearly 44 thousand deposits adding up to only 8.3 million dollars in the last 10 years.

What do these tags mean?
matches
The paper's claim is directly supported by a theorem in the formal canon.
supports
The theorem supports part of the paper's argument, but the paper may add assumptions or extra steps.
extends
The paper goes beyond the formal theorem; the theorem is a base layer rather than the whole result.
uses
The paper appears to rely on the theorem as machinery.
contradicts
The paper's claim conflicts with a theorem or certificate in the canon.
unclear
Pith found a possible connection, but the passage is too broad, indirect, or ambiguous to say the theorem truly supports the claim.

Reference graph

Works this paper leans on

30 extracted references · 30 canonical work pages · 1 internal anchor

  1. [1]

    Bitbucket - The Git solution for professional teams

    2018. Bitbucket - The Git solution for professional teams . Retrieved 20/12/2018 from https://bitbucket.org

  2. [2]

    CoinMarketCap - Cryptocurrency Market Capitalizations

    2018. CoinMarketCap - Cryptocurrency Market Capitalizations . Retrieved 23/12/2018 from https://coinmarketcap.com

  3. [3]

    GitHub - The world’s leading software development platform

    2018. GitHub - The world’s leading software development platform . Retrieved 20/12/2018 from https://github.com

  4. [4]

    GitLab - The first single application for the entire DevOps lifecycle

    2018. GitLab - The first single application for the entire DevOps lifecycle . Retrieved 20/12/2018 from https://gitlab.com

  5. [5]

    2017 Will Be Remembered As The Year Of Bitcoin

    2019. 2017 Will Be Remembered As The Year Of Bitcoin . Retrieved 12/01/2019 from https://bit.ly/2RPZ0iG

  6. [6]

    BitcoinWhosWho - Bitcoin address lookup, checker, and alerts

    2019. BitcoinWhosWho - Bitcoin address lookup, checker, and alerts . Retrieved 12/01/2019 from https://bitcoinwhoswho.com/

  7. [7]

    BlockchainInfo - Search the Blockchain

    2019. BlockchainInfo - Search the Blockchain . Retrieved 12/01/2019 from https: //blockchain.info/

  8. [8]

    Free Software Foundations - Ways to Donate

    2019. Free Software Foundations - Ways to Donate . Retrieved 12/01/2019 from https://www.fsf.org/about/ways-to-donate/

  9. [9]

    The Shift project

    2019. The Shift project. Retrieved 01/02/2019 from https://www.shiftnrg.org/

  10. [10]

    WalletExplorer - Smart Bitcoin block explorer

    2019. WalletExplorer - Smart Bitcoin block explorer . Retrieved 12/01/2019 from https://www.walletexplorer.com/

  11. [11]

    Yahoo Finance - Business Finance, Stock Market, Quotes, News

    2019. Yahoo Finance - Business Finance, Stock Market, Quotes, News . Retrieved 12/01/2019 from https://finance.yahoo.com/

  12. [12]

    Yazan Boshmaf, Husam Al Jawaheri, and Mashael Al Sabah. 2019. BlockTag: design and applications of a tagging system for blockchain analysis. In IFIP Security’19. Springer, 299–313

  13. [13]

    Jon Brodkin. 2014. Tech giants, chastened by Heartbleed, finally agree to fund OpenSSL. Retrieved 01/02/2019 from https://goo.gl/QXwPHu

  14. [14]

    Paul A David, Andrew Waterman, and Seema Arora. 2003. FLOSS-US the free/li- bre/open source software survey for 2003. Stanford Institute for Economic Policy Research (2003). https://goo.gl/JdU2Cp

  15. [15]

    DigitalOcean. 2018. A Seasonal Report on Developer Trends in the Cloud: Open Source Edition. https://goo.gl/riye9B

  16. [16]

    Free Software Foundation. 2019. Free Software Foundation receives $1 million donation from Pineapple Fund . Retrieved 01/02/2019 from https://goo.gl/dKvP9K

  17. [17]

    Rishab A Ghosh, Ruediger Glott, Bernhard Krieger, and Gregorio Robles. 2002. Free/libre and open source software: Survey and Study. Part IV: Survey of devel- opers. https://goo.gl/HztfwX

  18. [18]

    GitHub. 2018. About READMEs - User Documentation . Retrieved 23/12/2018 from https://help.github.com/articles/about-readmes/

  19. [19]

    GitHub. 2018. GitHub Activity Data. Retrieved 05/12/2018 from https://goo.gl/ d4AabN

  20. [20]

    GitHub. 2018. The State of the Octoverse . Retrieved 23/12/2018 from https: //octoverse.github.com

  21. [21]

    GitHub: arfon. 2016. Making open source data more available . Retrieved 23/12/2018 from https://goo.gl/jqJVyh

  22. [22]

    Google: Felipe Hoffa. 2016. GitHub on BigQuery: Analyze all the open source code . Retrieved 23/12/2018 from https://goo.gl/pRmwBS

  23. [23]

    A Hars and S OU. 2001. Working for Free?–Motivations of Participating in Open Source Projects, 00 (c), 1–9. In 34th Annual Hawaii International Conference on System Sciences (HICSS-34), Havaí . 25–39

  24. [24]

    Guido Hertel, Sven Niedner, and Stefanie Herrmann. 2003. Motivation of software developers in Open Source projects: an Internet-based survey of contributors to the Linux kernel. Research policy 32, 7 (2003), 1159–1177

  25. [25]

    Harry Kalodner, Steven Goldfeder, Alishah Chator, Malte MÃűser, and Arvind Narayanan. 2017. BlockSci: Design and applications of a blockchain analysis platform. Technical Report. arXiv:cs.CR/1709.02489

  26. [26]

    Ambarish Kumar. 2018. Easily Fund Open Source Projects With These Platforms . Retrieved 21/12/2018 from https://goo.gl/7WgiFJ

  27. [27]

    Steve Marquess. 2014. Of Money, Responsibility, and Pride. https://goo.gl/RCdMc8

  28. [28]

    Satoshi Nakamoto. 2008. Bitcoin: A peer-to-peer electronic cash system. (2008)

  29. [29]

    NetCraft. 2014. Half a million widely trusted websites vulnerable to Heartbleed bug. https://goo.gl/PMyNSH

  30. [30]

    Italo Vignoli. 2016. 200K thanks. Retrieved 12/1/2019 from https://goo.gl/g7zyq6 3For latest research outcomes, please visit https://qcri.github.io/cibr 8