A bibliometric analysis of Bitcoin scientific production

Aurelio F. Bariviera; Ignasi Merediz-Sol\`a

arxiv: 1906.08933 · v1 · pith:QM3T4DLDnew · submitted 2019-06-21 · 💻 cs.DL · q-fin.GN

A bibliometric analysis of Bitcoin scientific production

Ignasi Merediz-Sol\`a , Aurelio F. Bariviera This is my paper

Pith reviewed 2026-05-25 18:43 UTC · model grok-4.3

classification 💻 cs.DL q-fin.GN

keywords bitcoinbibliometric analysisscientific productionresearch trendsweb of scienceeconomicscomputer scienceblockchain

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The pith

A bibliometric study of 1162 papers maps Bitcoin research clusters and trends across economics, engineering, mathematics and computer science.

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

The paper conducts a bibliometric analysis limited to papers indexed in the Web of Science Core Collection whose topic is exactly 'bitcoin'. It seeks to identify research clusters, emerging topics and leading scholars while deliberately excluding other blockchain applications. This overview is presented as necessary because Bitcoin publications began only in 2012 yet already total 1162 items spanning multiple disciplines. The resulting map is intended to show the current state and direction of Bitcoin-specific scientific work.

Core claim

The scientific production on Bitcoin consists of 1162 papers indexed in the Web of Science Core Collection under the topic 'bitcoin' beginning in 2012; a bibliometric treatment of this corpus draws the landscape of research clusters, emerging topics and leading scholars in economics, engineering, mathematics and computer science.

What carries the argument

Bibliometric analysis performed on the set of Web of Science Core Collection papers whose topic field contains 'bitcoin'.

If this is right

Leading scholars and institutions working on Bitcoin become identifiable by citation and publication counts.
Emerging topics within Bitcoin research become visible for targeted follow-up studies.
Disciplinary clusters, for example the split between economic and computer-science approaches, are delineated.
The overall growth trajectory and magnitude of Bitcoin scientific output since 2012 is quantified.

Where Pith is reading between the lines

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

The same method could be reapplied in later years to track whether clusters shift as Bitcoin matures.
Newcomers to Bitcoin research could use the identified leading authors and clusters as an entry map.
Comparison of this Bitcoin-only map with a parallel blockchain-wide analysis would highlight what is distinctive about Bitcoin studies.

Load-bearing premise

Restricting the search to papers indexed in the Web of Science Core Collection whose topic is 'bitcoin' sufficiently captures the relevant scientific production on Bitcoin.

What would settle it

Discovery of a large number of peer-reviewed Bitcoin papers published outside Web of Science or not captured by a topic search for the single word 'bitcoin' would show the drawn landscape to be incomplete.

Figures

Figures reproduced from arXiv: 1906.08933 by Aurelio F. Bariviera, Ignasi Merediz-Sol\`a.

read the original abstract

Blockchain technology, and more specifically Bitcoin (one of its foremost applications), have been receiving increasing attention in the scientific community. The first publications with Bitcoin as a topic, can be traced back to 2012. In spite of this short time span, the production magnitude (1162 papers) makes it necessary to make a bibliometric study in order to observe research clusters, emerging topics, and leading scholars. Our paper is aimed at studying the scientific production only around bitcoin, excluding other blockchain applications. Thus, we restricted our search to papers indexed in the Web of Science Core Collection, whose topic is "bitcoin". This database is suitable for such diverse disciplines such as economics, engineering, mathematics, and computer science. This bibliometric study draws the landscape of the current state and trends of Bitcoin-related research in different scientific disciplines.

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.

Desk Editor's Note private letter to a colleague

Standard bibliometric snapshot of 1162 WoS papers on 'bitcoin'; useful narrow map but database limits make broader claims shaky.

read the letter

This paper runs a standard bibliometric analysis on Bitcoin papers indexed in Web of Science Core Collection under the topic 'bitcoin', ending up with 1162 records from 2012 onward. It breaks out publication growth, subject categories, top authors, countries, and some keyword trends. Nothing in the approach is novel methodologically, but the specific dataset and focus give a clean descriptive picture of that slice of literature. The counts and basic distributions look reproducible from the stated search, and the paper is explicit that it excludes other blockchain work and sticks to WoS. That transparency is helpful. The main soft spot is coverage. Bitcoin research began heavily in computer science with conference papers, workshops, and arXiv preprints that WoS indexes poorly. Searching only the exact term 'bitcoin' also risks missing papers that use 'BTC', 'Bitcoin protocol', or related phrasing. No cross-check against Scopus, arXiv, or alternative terms is reported, so the observed clusters, leading scholars, and disciplinary balance could shift if the net were cast wider. The authors do not overclaim universality, but the title and abstract still frame it as mapping 'Bitcoin-related research in different scientific disciplines,' which overreaches given the constraints. For readers who need a quick, citable overview of the indexed economics and finance side of Bitcoin publications, this delivers. It is not going to change how anyone models the field, but the data extraction is straightforward and the results are falsifiable by repeating the search. I would send it to peer review with a request for a short methods appendix on search sensitivity and a clearer statement of scope in the abstract.

Referee Report

1 major / 0 minor

Summary. The manuscript presents a bibliometric analysis of 1162 papers from the Web of Science Core Collection with topic 'bitcoin' (first appearing in 2012) to map research clusters, emerging topics, and leading scholars in Bitcoin-related work across disciplines such as economics, engineering, mathematics, and computer science, while excluding other blockchain applications.

Significance. If the search strategy yields a representative sample, the work supplies a targeted descriptive overview of an emerging interdisciplinary field, using standard bibliometric techniques on a narrowly scoped topic.

major comments (1)

[Abstract] Abstract (search description): the restriction to WoS Core Collection papers whose topic is exactly 'bitcoin' is presented without sensitivity analysis, alternative-term testing (e.g., 'BTC'), or cross-database validation against conference/preprint sources common in computer science and engineering. This choice is load-bearing for the central claim that the resulting clusters and trends represent the landscape of Bitcoin scientific production.

Simulated Author's Rebuttal

1 responses · 0 unresolved

Thank you for the constructive feedback on our manuscript. We address the referee's major comment below and outline the revisions we will make.

read point-by-point responses

Referee: [Abstract] Abstract (search description): the restriction to WoS Core Collection papers whose topic is exactly 'bitcoin' is presented without sensitivity analysis, alternative-term testing (e.g., 'BTC'), or cross-database validation against conference/preprint sources common in computer science and engineering. This choice is load-bearing for the central claim that the resulting clusters and trends represent the landscape of Bitcoin scientific production.

Authors: We agree that the search strategy requires additional justification to support the claim of representing the Bitcoin research landscape. The manuscript intentionally limited the scope to the exact term 'bitcoin' in the Web of Science Core Collection to exclude other blockchain applications and to ensure coverage across economics, engineering, mathematics, and computer science. However, the paper does not include sensitivity analysis for alternative terms such as 'BTC', nor validation against non-WoS sources like conference proceedings or preprints. In the revised version, we will add a dedicated paragraph in the methods section explaining the rationale for the chosen database and term, while explicitly noting the limitations regarding potential underrepresentation of computer science outputs and the lack of cross-database checks. revision: yes

Circularity Check

0 steps flagged

No significant circularity; analysis is data-driven from external source

full rationale

The paper conducts a standard bibliometric analysis by querying an external database (Web of Science Core Collection) for papers with topic 'bitcoin' and then describing clusters, trends, and scholars from the resulting dataset. No equations, fitted parameters, predictions, or self-citations appear in the provided text that would reduce any claim to an input by construction. The central output (landscape of Bitcoin research) is generated directly from the retrieved records rather than from any internal definition or prior self-referential result. This matches the default expectation of a non-circular descriptive study.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

Relies on standard bibliometric search and clustering techniques applied to a new corpus; no free parameters, invented entities, or non-standard axioms stated.

axioms (1)

domain assumption Web of Science Core Collection is a suitable database for capturing Bitcoin research across economics, engineering, mathematics, and computer science.
Invoked in abstract to justify data source choice.

pith-pipeline@v0.9.0 · 5671 in / 987 out tokens · 17640 ms · 2026-05-25T18:43:44.677763+00:00 · methodology

discussion (0)

Reference graph

Works this paper leans on

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Wei, G. (2019). A bibliometric analysis of the top ﬁve economics journals during 20122016. Journal of Economic Surveys , 33(1):25–59. Yermack, D. (2013). Is bitcoin a real currency? an economic appraisal. Working Paper 19747, National Bureau of Economic Research. Yli-Huumo, J., Ko, D., Choi, S., Park, S., and Smolander, K. (2016). Where Is Current Researc...

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[1] [1]

S., Eichengreen, B., O’Rourke, K

Almunia, M., B´ en´ etrix, A. S., Eichengreen, B., O’Rourke, K. H., and Rua, G. (2009). From Great Depression to Great Credit Crisis: Similarities, Dif- 19 ferences and Lessons. NBER Working Papers 15524, National Bureau of Economic Research, Inc. Andrikopoulos, A., Samitas, A., and Kostaris, K. (2016). Four decades of the journal of econometrics: Coautho...

work page 2009

[2] [2]

and Cuccurullo, C

Aria, M. and Cuccurullo, C. (2017). bibliometrix: An r-tool for comprehensive science mapping analysis. Journal of Informetrics , 11(4):959–975. Aslanidis, N., Bariviera, A. F., and Martinez-Iba˜ nez, O. (2019). An analysis of cryptocurrencies conditional cross correlations. Finance Research Letters, 31:130–137. Balcilar, M., Bouri, E., Gupta, R., and Rou...

work page 2017

[3] [3]

Bariviera, A. F. (2017). The ineﬃciency of Bitcoin revisited: A dynamic ap- proach. Economics Letters, 161:1–4. Bariviera, A. F., Zunino, L., and Rosso, O. A. (2018). An analysis of high- frequency cryptocurrencies prices dynamics using permutation-information- theory quantiﬁers. Chaos: An Interdisciplinary Journal of Nonlinear Science , 28(7):075511. Bar...

work page 2017

[4] [4]

B¨ ohme, R., Christin, N., Edelman, B., and Moore, T. (2015). Bitcoin: Eco- nomics, Technology, and Governance. Journal of Economic Perspectives , 29(2):213–238. B¨ ohme, R., Christin, N., Edelman, B., and Moore, T. (2015). Bitcoin: Eco- nomics, technology, and governance. Journal of Economic Perspectives , 29(2):213–38. Bonilla, C. A., Merig´ o, J. M., a...

work page 2015

[5] [5]

bibliometrics

Broadus, R. N. (1987). Toward a deﬁnition of “bibliometrics”. Scientometrics, 12(5):373–379. Cancino, C., Merig´ o, J. M., Coronado, F., Dessouky, Y., and Dessouky, M. (2017). Forty years of computers & industrial engineering: A bibliometric analysis. Computers & Industrial Engineering , 113:614 –

work page 1987

[6] [6]

M., Son, L

20 Chatterjee, J. M., Son, L. H., Ghatak, S., Kumar, R., and Khari, M. (2018). Bitcoin exclusively informational money: a valuable review from 2010 to

work page 2018

[7] [7]

Cheah, E.-T

Quality & Quantity , 52(5):2037–2054. Cheah, E.-T. and Fry, J. (2015). Speculative bubbles in bitcoin markets? an empirical investigation into the fundamental value of bitcoin. Economics Letters, 130:32 –

work page 2037

[8] [8]

Chung, K. H. and Cox, R. A. K. (1990). Patterns of productivity in the ﬁnance literature: A study of the bibliometric distributions. The Journal of Finance , 45(1):301. Ciaian, P., Rajcaniova, M., and dArtis Kancs (2016). The economics of bitcoin price formation. Applied Economics, 48(19):1799–1815. Clarivate Analytics (2018a). InCites Indicators Handbook...

work page 1990

[9] [9]

F., Carvalho, F

Costa, D. F., Carvalho, F. d. M., and Moreira, B. C. d. M. (2019). Behavioral economics and behavioral ﬁnance: A bibliometric analysis of the scientiﬁc ﬁelds. Journal of Economic Surveys , 33(1):3–24. Cronin, B. (2001). Hyperauthorship: A postmodern perversion or evidence of a structural shift in scholarly communication practices? Journal of the American ...

work page 2019

[10] [10]

and Spellerberg, I

Fedor, P. and Spellerberg, I. (2013). ShannonWiener Index. Reference Module in Earth Systems and Environmental Sciences . Hart, P. E. (1971). Entropy and Other Measures of Concentration. Journal of the Royal Statistical Society.Series A (General) , 134(1):pp. 73–85. Hernando, A. and Plastino, A. (2012). Thermodynamics of urban population ﬂows. Physical Re...

work page 2013

[11] [11]

Katsiampa, P. (2019). Volatility co-movement between Bitcoin and Ether. Fi- nance Research Letters, forthcoming. Khan, M. A. and Salah, K. (2018). Iot security: Review, blockchain solutions, and open challenges. Future Generation Computer Systems , 82:395 –

work page 2019

[12] [12]

Klein, T., Pham Thu, H., and Walther, T. (2018). Bitcoin is not the New Gold A comparison of volatility, correlation, and portfolio performance. International Review of Financial Analysis , 59:105–116. Korom, P. (2019). A bibliometric visualization of the economics and sociology of wealth inequality: a world apart? Scientometrics. Kuo, T.-T., Kim, H.-E., ...

work page 2018

[13] [13]

W., Mart´ ın, M

Lamberti, P. W., Mart´ ın, M. T., Plastino, A., and Rosso, O. A. (2004). Intensive entropic non-triviality measure. Physica A, 334(12):119–131. Liu, J. (2016). Bitcoin Literature: a Co-Word Analysis. In Cermakova, K., edi- tor, 6th Economics & Finance Conference, OECD, Paris, number September, pages 262–272, Paris. International Institute of Social and Ec...

work page 2004

[14] [14]

Miers, I., Garman, C., Green, M., and Rubin, A

Technology Analysis & Strategic Management, 30(9):1029–1045. Miers, I., Garman, C., Green, M., and Rubin, A. D. (2013). Zerocoin: Anony- mous distributed e-cash from bitcoin. In 2013 IEEE Symposium on Security and Privacy, pages 397–411. Nadarajah, S. and Chu, J. (2017). On the ineﬃciency of bitcoin. Economics Letters, 150:6 –

work page 2013

[15] [15]

Nakamoto, S. (2009). Bitcoin: A peer-to-peer electronic cash system. https: //bitcoin.org/bitcoin.pdf/. Accessed: 2016-12-27. Petersen, K., Feldt, R., Mujtaba, S., and Mattsson, M. (2008). Systematic mapping studies in software engineering. In Proceedings of the 12th Inter- national Conference on Evaluation and Assessment in Software Engineering , EASE’08...

work page 2009

[16] [16]

Urquhart, A. (2017). Price clustering in bitcoin. Economics Letters, 159:145 –

work page 2017

[17] [17]

van Eck, N. J. and Waltman, L. (2010). Software survey: Vosviewer, a computer program for bibliometric mapping. Scientometrics, 84(2):523–538. Van Hout, M. C. and Bingham, T. (2014). Responsible vendors, intelligent consumers: Silk road, the online revolution in drug trading. International Journal of Drug Policy , 25(2):183 –

work page 2010

[18] [18]

Wei, G. (2019). A bibliometric analysis of the top ﬁve economics journals during 20122016. Journal of Economic Surveys , 33(1):25–59. Yermack, D. (2013). Is bitcoin a real currency? an economic appraisal. Working Paper 19747, National Bureau of Economic Research. Yli-Huumo, J., Ko, D., Choi, S., Park, S., and Smolander, K. (2016). Where Is Current Researc...

work page 2019