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Abstract
Drawing on an empirical study of cryptocurrency white papers, this paper proposes an actor-based taxonomy of cryptocurrency blockchains. First, it describes the evolution of blockchain architecture with reference to the economic services that blockchains supply. Second, it discusses the socio-technical platform of blockchains as proposed in cryptocurrency white papers. Third, it analyses the socio-economic consequences of these technically diverse blockchain platforms, by proposing a taxonomy of their digital architectures in reference to two groups of actors that maintain blockchain infrastructure: transactioners and accountants. Defining cryptocurrency as data money, and locating cryptocurrency ownership as the possession of an exclusive right to move data privately in a public or private space, the paper describes a blockchain as a digital actor-network platform that makes it possible to define and distribute these data transfer rights.
Acknowledgements
The author would like to thank Janet Roitman, İlker Birbil, Donald MacKenzie, William Milberg, Vincent Lepinay, Burak Arıkan, Gözde Güran, Electra01, Clement Gasull, participants in Platform Economies Reading Group at the New School, students who took my classes at the New School, and two anonymous reviewers for their contribution, and Sevde Ünal, Collin McClain, Hasine Güler and Nina Macaraig for editorial and research assistance and İlker Birbil for assistance with text analysis with R.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Koray Caliskan is Associate Professor of Strategic Design and Management at Parsons School of Design, the New School. He received his PhD with distinction from New York University, for which he won the Malcolm Kerr Social Science Award from MESA. His book Market threads: How cotton framers and traders create a global commodity (Princeton University Press, 2010) focused on global commodity markets. Currently, he works on platform design, cryptocurrecies and blockchains.
Notes
1 This paper draws on www.coinmarketcap.com closing price data, cross-checked with CBOT and CME data. GDP data source is World Bank (Citation2020).
2 I would like to thank Janet Roitman for drawing my attention to such a possibility.
3 Digibyte, Dogecoin, GAS, Huobi Token and Monacoin have no formal white papers in this paper’s top 100 list, yet their blockchains are included in the analysis. The raw data of all of these white papers and the R code can be found here: https://github.com/sibirbil/DataMoney https://doi.org/10.5281/zenodo.4126559.
4 These cryptocurrencies are Aelf, Aeternity, Aion, Allsports, Ardor, Ark, Augur, Bancor, Basic Attention Token, Binance Coin, Bitcoin Cash, Bitcoin Diamond, Bitcoin Gold, Bitcoin Private, Bitcoin, Bitshares, Bytecoin, Bytom, Cardano, Centrality, Cortex, Cryptonex, Cybermiles, Dash, Decred, Dentacoin, Digibyte, DigixDAO, Dogecoin, Dragonchain, Elastos, Electroneum, Enigma, EOS, Ethereum Classic, Ethereum, Ethos, Funfair, Fusion, GAS, Golem, Gxchain, Huobi Token, Hypercash, ICON, Internet of Services, Kin, Komodo, Kucoin Shares, Kybernetwork, Lisk, Litecoin, Loom Network, Loopring, MaidSafeCoin, Maker, Mıota, Mithril, Mixin, MOAC, Monacoin, Monero, Nano, Nebulas, Nem, NEO, Nexusi, Nuls, OmiseGo, Ontology, 0x, PIVX, Polymath, Populous, Qash, Qtum, Rchain, Reddcoin, SiaCoin, Skycoin, Status, Steem, Stellar, Stratis, Substratum, Syscoin, Tether, Theta Token, Tron, Vechain, Verge, Veritaseum, Waltonchain, Wanchain, Waves, Waykichain, XRP and Zcash, Zcoin, Zilliqa.
5 I define public as a sphere whose usage and entrance cannot be limited to a select group of individuals. A private sphere, can be used by many individuals and groups, such as a private club, but cannot qualify as public for it has a formal boundary that controls entry.
6 Computer scientists such as Don Patterson also see cryptocurrency as a possession of an exclusive right to transfer data. For an excellent discussion of data money transactions from a computer science perspective see (Patterson, Citation2014).
7 A few of these publications use the computer screen as page unit. In order to compare their length and page statistics, three white papers were formatted to fit into a US legal-size page.
8 The author identified the authors’ gender from their first names, LinkedIn data and photographs, yet the paper makes no assumption regarding the assumed gender positions these writers might have taken.
9 Core social scientific categories are stemmed to represent white papers’ foci. For example, finance and financial were plotted together.
10 Ontology white paper locates its blockchain as a bridge between ‘the real world’ and ‘distributed data systems’.
11 The technical literature concerning cryptocurrencies rightfully locates private blockchains as permissioned blockchains that locate authority nodes for the accounting process (Narayanan & Clark, Citation2017).