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ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue I, January 2026

Footprints of Cryptocurrency: A Bibliometric Review

Vishwabandhu Bharti

*, Dr. Sanjay Kumar

Research Scholar Department of Management, Central University of Rajasthan Bandarsindri, Dist.-

Ajmer – 305817, Rajasthan, India

Assistant Professor Department of Management, Central University of Rajasthan Bandarsindri, Dist.-

Ajmer – 305817, Rajasthan, India

*Corresponding Author

DOI:

https://doi.org/10.51583/IJLTEMAS.2026.1501000101

Received: 31 January 2025; Accepted: 05 February 2026; Published: 18 February 2026

ABSTRACT

The growing popularity, the exponentially expanding market size, and the volatility of Cryptocurrency are

gaining the attention of all, whether it is investors, policymakers, miners, or academicians. So, this paper has

used Bibliometric analysis to explore the existing works of literature in the area of Business, Finance, and

Economics. We have reviewed and analysed 1344 articles extracted from the Web of Science core collection,

Clarivate Analytics of the period from 2011 to mid-2022 using VOSviewer and Biblioshiny (Biblimetrix: R

package) analytical tools. This paper has presented citations, publications, and the impact of sources, documents,

authors, organizations, countries, etc., along with their relationships with the help of tables, charts, and network

diagrams. The analysis shows exponential growth in the last 4-5 years. Bitcoin and Cryptocurrency (or

Cryptocurrencies) are the most frequent keywords. With many ups and downs, cryptocurrency is maintaining

its pace with a gradual increase in its acceptability worldwide.

Keywords: Cryptocurrency, Bitcoin, Bibliometric analysis, Biblioshiny, VOSviewer

JEL Classification

INTRODUCTION

In the world of digitization, everything is going digital. The currency is also taking a digital face. Cryptocurrency

also is the result of this digitization race. Cryptocurrency is a type of decentralized digital currency which had

presence for a long time but has come into the picture after the inception of Bitcoin in 2008, which was developed

by a pseudonymous developer Satoshi Nakamoto. The first commercial transaction involving Bitcoin happened

in 2010 (History of the Cryptocurrency market in India, 2021). After that, in 2011, other cryptocurrencies like

Namecoin, Litecoin, etc. commonly known as Altcoin (Cryptocurrencies other than Bitcoin), started to emerge.

In such a short span of a decade, cryptocurrency has exploded onto the scene and has grown at an ever-increasing

rate.

As the topic (cryptocurrency) has attracted investors, academicians, writers, etc. towards it because of its unique

features. It is becoming impossible to keep up with everything being published due to the rapid increase in

academic publications (Briner & Denyer, 2012). This really hampers the ability to accumulate knowledge and

to actively collect evidence through the set of previous research works. Therefore, Literature Review studies are

becoming crucial in synthesizing past research findings for effective use of the existing knowledge base,

advancing a line of research and providing evidence-based insight into the practice of exercising and sustaining

professional judgment and expertise (Rousseau, 2012). So, this paper has used one of the popular review

techniques known as Bibliometric Analysis. Bibliometric analysis is the use of statistical methods to analyse the

bibliometric publications data such as peer-reviewed journals, articles, books, conference proceedings,

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periodicals, reports and related documents. It is widely used to present the relations of research domains with

quantitative methods (Ali et al., 2021)

Development

The idea of cryptocurrency begun to evolve in the late eighties. Digicash invented by David Chaum was an early

form of decentralized e-money. Decentralization which became the central characteristics of the modern

cryptocurrencies. After that there were many attempts to create cryptocurrencies and some of them got success

too. Bitgold was one of them, which is regarded as predecessor to Bitcoin. The cryptocurrency idea got solidified

after the inception of Bitcoin in 2008. Since 2010, cryptocurrency in the form of bitcoin stated its role playing

in the commercial world with the historical transaction of two pizzas for 10,000 bitcoins. Other cryptocurrencies

i.e., altcoins were continuously being created along with other related developments. Many cryptocurrency

exchanges were created, and ATMs were installed to support its commercial transactions. Organisations to

support its development and the magazines for promotion were also created. Cryptocurrency derivatives were

also created to boost its trade by actual price discovery and future predictions. Everything was good with minor

glitches in the form of hacks and policy makers’ regulations and prohibitions. Growing acceptance by many

major corporates and the increasing confidence among the investors pushed the Bitcoin price to, its highest till

date of $20,00 per bitcoin.

Very soon after the hike, rumours regarding the ban of cryptocurrency, were spreading

very quickly. Initial coin offering and token sales were banned by many large companies like Facebook, Google,

Twitter, etc. The largest cryptocurrency OTC market of Japan was hacked. And there were many instances of

theft and losses were being reported. These negative incidences caused the demotivation among the investors,

which resulted the crisis to take place in the early 2018. After the crisis extensive research and development

works started to know the reason of the crisis and to find the way to improve the situation. Many corporates

started to adopt Blockchain as an application. All these continued, which caused the improvement in the

cryptocurrency market condition and pushed the demand of qualified developers and miners too. These types of

developments revived the confidence of the investors so boldly that caused a boom in 2021, where Bitcoin price

touched its all time high of $69,000 per coin. As every extreme has a limit, so evidenced in the case of

cryptocurrency. After just some time of this big hike, in 2022 a big correction in the bitcoin price took place.

There were many reasons behind it. Some of them are- Chinese ban over cryptocurrency, possible hikes in FED

rate as hinted in Dec. 2021, stock market correction, panic selling, profit booking, etc.

The Beginning

1989

Digicash – An early form of decentralized e-money

invented by David Chaum.

1998

Bitgold (predecessor to Bitcoin) is

created by Nick Szabo.

2008

 Inception of Bitcoin

 First Bitcoin exchange “Bitcoin Market” was

established.

2009

Bitcoin is mined and transacted

for the first time.

Gaining Recognition and

Acceptance

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Growth

2017

 Bitcoin hit the price of

$20,000 –highest till the

date

 Launch of Bitcoin Futures

2010

First commercial tangible transaction took place: two

Pizzas for 10,000 Bitcoins.

2011

 First acceptance of Bitcoin by

an online store.

 Litecoin and Namecoin

stormed the scene.

 Bitcoin = 1USD

2012

Bitcoin magazine was launched, and Bitcoin

foundation was established.

2013

 DogeCoin, the flagship memcoin was

created.

 First Bitcoin ATM was launched at

Vancouver B.C.

 FBI shutdown Silk Routes and

confiscated 26,000 bitcoins.

2014

 Mt. Gox was hacked again of $473 million.

 By the end of the year several companies

like Microsoft, PayPal started to accept

Bitcoin.

2015

Etherium arrived with smart contract

and rivalled Bitcoin.

2016

 DAO – A blockchain organisation based on

Etherium lost $50 million

 Bitfinex bitcoin exchange was hacked

for $66 million

Crisis Period

Recovery

2018

 Coincheck (A Japanese exchange)

was hacked for $534 million

 In December Bitcoin= $3,400

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2022

 China banned Cryptocurrency

 Central African Republic- 2

country

to adopt Bitcoin as legal tender

 Bitcoin = $21,600

 No. of Cryptocurrencies = 20,726

 Market cap = $1 Trillion

 No. of exchange

Figure 1: Timeline of Cryptocurrency

Regulations and Legal status

Seeing the cryptocurrencies’ exponentially growing popularity and the probable threats attached to them,

regulations regarding them have continuously been tightened.

Financial Action Task Force (FATF) has defined cryptocurrency-related services as virtual assets services

providers (VASPs) and recommended that they have to be regulated with the same money laundering and know-

your-customer (KYC) requirements as financial institutions (cryptocurrency, 2021)

Every country is trying to regulate cryptocurrencies. In this row, China moved a step ahead and banned financial

institutions and payment companies from being able to provide cryptocurrency transactions-related services in

2018. Again in 2020, Chinese government declared all cryptocurrency transactions of any kind as illegal.

South Korea implemented new legislation regarding all digital asset managers, providers and exchanges to be

registered with the Korea Financial Intelligence Unit to operate in South Korea. India too in 2018, issued circular

banning banks and NBFCs from dealing in virtual currency and providing such services to people associated

with them.

2019

7 major crypto exchanges were

hacked

 Extensive research and

development started on

Blockchain

 Amazon and Walmart started

using Blockchain as application

2020

Adoption of Blockchain as an application

continued, so the demand for qualified

developers.

Balancing

Boom

2021

 Market cap of

Cryptocurrency passed $3

trillion

 El. Salvador recognized

Cryptocurrency as legal

tender



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Although Supreme Court set aside this virtual ban on cryptocurrencies the policymakers are continuously trying

to hinder the cryptocurrency growth in India.

So, they took digital currency gains in the purview of the high-income tax bracket and proposed to issue an

official digital currency of its own to minimize the crypto flow in the country (cryptocurrency regulations in

India: a brief history, 2020).

In the midst of the tightening of crypto regulations race, there are some countries also like El. Salvador and the

South African Republic have recognized cryptocurrency as legal tender for unrestricted operations in the country

(cryptocurrency, 2021)

METHODOLOGY

The present study employs the systematic methodological approach to ensure comprehensive coverage with

reproducible results of the existing literature.

Systematic reviews aid in familiarizing with the present state of the art and in the identification of research gaps

in that field (Tranfeld et al. 2003; Rousseau et al. 2008). The authors discuss the complete methodological

process in the following sub-sections.

Literature retrieval and selection (Data)

The present paper works with the bibliometric data extracted from Web of Science Core Collection (WoS),

Clarivate Analytics. Web of Science database is the oldest and one of the largest databases with a wide range of

academic resources in multiple disciplines.

To avoid the chances of missing the research papers authors use different keywords, cryptocurrency, bitcoin,

cryptocurrencies, crypto currency and crypto currencies with “or” operator. Asterisk (*) is not used because it

covers some extra articles outside the purview of our interest i.e., cryptocurrency.

We use “Topic” search field which covers the title, abstract, author keywords and keywords plus which provides

enhanced coverage of the relevant articles.

By considering the whole-time range of 2011 – mid-2022 without any filter we have found 3637 documents.

After applying the filter “Articles” in Document types we found 3312 documents and by applying “Business,

Business Finance, Economics, Management and Social Sciences Interdisciplinary” in Web of Science

categories, found 1344 documents. Since all the documents available (1344) are in English language only, so

we haven’t used “Language “filter”.

After that, we exported the bibliometric data of all the selected documents in “Plain Text file” by selecting “Full

record and Cited references”. The plain text file is selected because it is supported by both the bibliometric

analytical tools “VOSviewer” and “Biblioshiny “.

Web of Science allows exporting a maximum of 500 records at one time. So, we have exported three times for

all the records by selecting different ranges of records. Biblioshiny does not allow selecting multiple files while

loading data on it. So, we make a consolidated file of all three plain text files by just copying and pasting the

second and third files into the first one.

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*Selected all available

Figure 2- Data extraction and processing mechanism

Tools

This paper utilises two important and popular bibliometric analysis tools VOSviewer and Biblioshiny.

VOSviewer is a freely available Java-based application developed by Van ECK and Waltman for analysing and

visualising citation networks of scientific collections (Massimo Aria & Corrado Cuccurullo, 2017). Biblioshiny

is a part of the “R” packages for bibliometric analysis. It is also available without any charges.

Results and Discussion

Descriptive Analysis

Description

Results

Timespan of study

2011:2022

Number of Sources (Journals, Books, etc.)

221

Number of Documents

1344

Annual Growth Rate % of documents

68.16

Document Average Age

1.68

Average citations per doc

24.54

References

31838

Data Extraction

Data Screening

Data Export

Analysis

Searching documents

Search Field- Topic

Keywords-

Cryptocurrency

Bitcoin

Cryptocurrencies

Crypto currency

Crypto currencies

(Output- 3637 documents)

Applying Filters

Document Types- Articles

WOS Categories- Cryptocurrency,

Bitcoin, Cryptocurrencies, Crypto

currency, Crypto currencies

Language- English*

Publication Years- 2011-2022*

(Output- 1344 articles)

Data Screening

Relevancy check of articles

(Output-1344 Articles)

Analysis

Tools – VOSviewer

Biblioshiny: R Package

Data Export

By selecting

Types of files

Record range

Content

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Table 1: Annual scientific production and citation

DOCUMENT CONTENTS

Keywords Plus (ID)

1174

Author's Keywords (DE)

2843

AUTHORS

Authors

2383

Authors of single-authored docs

195

AUTHORS COLLABORATION

Single-authored docs

242

Co-Authors per Doc

2.75

International co-authorships %

43.45

Documents type

Articles only

Year

Annual production

Mean Total Citation per article

Mean Total Citation per year

2011

2.00

0.18

2012

0.00

2013

0.00

2014

6.50

0.81

2015

187.42

26.77

2016

149.00

24.83

2017

126.83

25.37

2018

85.28

21.32

2019

188

41.61

13.87

2020

257

25.14

12.57

2021

356

9.14

2022

304 *

2.24*

It is evident from the table 1 that the first article has published in 2011 and then shown stagnancy in

production for a few years. But from 2015 there is exponential growth in the publication year after year which

shows the pace of the growing popularity of Cryptocurrencies. It shows an annual growth rate of 68.16%.

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*AU CO- Author’s country, DE- Author Keyword, AU- Author

Figure 3 – Three Field plot of authors, authors’ countries and author keywords

Three Field plot is the diagrammatic representation of the relationship among the three terms. It helps in

understanding the relationship among the terms along with the breadth and depth of the relationship. Fig.3

shows the three-field plot of Authors, Authors’ country and Author Keywords. China has the biggest share

among all the countries which is evident from the longest rectangle shown with China. It means China’s

scientific production related to cryptocurrency is maximum. Similarly, it can be interpreted that Bitcoin is

the most frequently used Keyword and author Elie Bouri has the maximum number of articles in this field.

The width of the links shows the proportion of the relationship shared by the pair. So, it can be concluded

that China’s maximum work in this field is related to Bitcoin which also covers the maximum number of

articles on bitcoin. The most productive author Elie Bouri also has the maximum number of papers related to

bitcoin. China has contributed to almost all the fields related to the given keywords that are implied from the

direction of the links.

Source Analysis

Table 2 Most relevant Sources

Sr. No.

Sources

Articles

FINANCE RESEARCH LETTERS

250

ECONOMICS LETTERS

RESEARCH IN INTERNATIONAL BUSINESS AND

FINANCE

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INTERNATIONAL REVIEW OF FINANCIAL

ANALYSIS

APPLIED ECONOMICS LETTERS

NORTH AMERICAN JOURNAL OF ECONOMICS AND

FINANCE

TECHNOLOGICAL FORECASTING AND SOCIAL

CHANGE

APPLIED ECONOMICS

FINANCIAL INNOVATION

10.

JOURNAL OF INTERNATIONAL FINANCIAL

MARKETS INSTITUTIONS & MONEY

Table 2 represents the list of the top 10 sources of articles in the selected field. Out of 221 sources of

publications, the top 10 journals have published a total of 684 documents which is approximately 51% of the

total publications of 1344. Only Finance Research Letters has published 18.6% of the total documents in this

area.

Figure 4- Most Local Cited Sources

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Citations are counted in two ways one is Global and the other is Local. A local citation is the number of times

a document is cited by others within the selected group of documents. For here the group of 1344 articles is

considered for the local citations.

On the other hand, Global citation is the number of times a document is cited by any of the other documents

in the Document repository or Database. In this paper, whole Web of Science database documents is

considered for the Global citations. Finance Research Letters is positioned at the top in terms of both local

as well as global citations (Total citations). Others in the row are Economics Letters, International Review of

Financial Analysis, etc. which are shown in Figure 4 and Table 3.

Table 3 Source Impact

Element

index

start

FINANCE RESEARCH

LETTERS

6.714

8077

197

2016

ECONOMICS LETTERS

5282

2015

INTERNATIONAL REVIEW

OF FINANCIAL ANALYSIS

2413

2016

RESEARCH IN

INTERNATIONAL

BUSINESS AND FINANCE

3.333

1485

2017

TECHNOLOGICAL

FORECASTING AND

SOCIAL CHANGE

2.667

817

2017

JOURNAL OF

INTERNATIONAL

FINANCIAL MARKETS

INSTITUTIONS & MONEY

1.625

1137

2015

NORTH AMERICAN

JOURNAL OF ECONOMICS

AND FINANCE

415

2019

QUARTERLY REVIEW OF

ECONOMICS AND

FINANCE

2.4

602

2018

APPLIED ECONOMICS

1059

APPLIED ECONOMICS

LETTERS

550

*There is difference between the number of publications and the total number of articles of sources because

of the presence of early access articles (It cannot be ignored because its number is 104 (more than 8%) that

is significant for the review paper)

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Source Dynamics

Figure 5 – Source Dynamics

Forbes is the oldest source producing the first article in 2011. After that Island Studies Journal published 2nd

article after a long duration of about 3 years. After that, several sources started coming into the picture. Figure

5 has shown a chart of the source dynamics of top articles... Most of the sources are showing a sudden upward

bend from 2018. It is because of the Cryptocurrency crisis that happened in 2018. The eagerness of knowing the

reality behind the crisis and the prospects of Cryptocurrencies led to the production of a large number of articles.

Finance Research Letters is showing much higher growth relative to the others in the chart. It started publishing

in this field in 2016 and got momentum very quickly by publishing a huge number of articles related to the field.

This is clearly visible through its steeply sloped graph. If we look at the source impact Finance Research Letters

topped once again topped in the list with attractive figures in all H, G and M indices. “Economics Letters” and

“International Review of Financial Analysis” are standing at second and third positions in the list.

Table 4 Most Relevant Authors

Authors

No. of Documents

Percentage

BOURI E

3.57

CORBET S

2.38

ROUBAUD D

2.00

LUCEY B

1.64

YAROVAYA L

1.64

SENSOY A

1.34

SHAHZAD SJH

1.34

URQUHART A

1.34

GUPTA R

1.19

NAEEM MA

1.19

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Table 5 Most Local Cited Authors

Author

Local Citations

BOURI E

1727

ROUBAUD D

1621

LUCEY B

1019

CORBET S

968

URQUHART A

868

GUPTA R

639

DYHRBERG AH

569

YAROVAYA L

561

MOLNAR P

522

LAU CKM

471

Table 4 displays the list of the top 10 most productive authors in the field. These ten authors have cumulatively

produced 237 documents out of 1344, which is 17.63 % of the total. Elie Bouri is at the top of the list with 48

(3.57%) documents. Corbet S. and Roubaud D. stand at the second and third positions in the list. If we talk about

the citations that are displayed in table 5 and table 6. Bouri E. is at the first position in terms of Local as well as

Total citations. It means he is the most cited authors among the selected articles as well as in the overall WOS

Database for the selected field. Roubaud D. holds the second position in terms of local and total citations.

Table 6 Authors’ Impact

Element

h_index

g_index

m_index

PY_start

BOURI E

3349

2017

ROUBAUD D

3115

2017

CORBET S

1974

2018

LUCEY B

3.2

1942

2018

GUPTA R

2.167

1258

2017

SENSOY A

528

2019

URQUHART A

1.714

1472

2016

SHAHZAD

SJH

2.75

788

2019

TIWARI AK

1.833

724

2017

KATSIAMPA P

897

Impact is calculated on the basis of different factors in which number of publications, total citation, ranks in

different indices are important. Here three indices are considered that are H index, G index and M index. Jorge

E. Hirsch, a physicist at UCSD suggested H-index in 2005. H index is the number at which the number of papers

is equal to the citations counted after arranging all the papers of concerned author in descending order of

citations. It is widely used index. But it does not consider the quality of papers, number of authors, position of

authors in the author’s list etc. It is independent of duration of academic’s career.

Because of this, relatively new author with same productivity is assigned with lower h-index. To overcome this

limitation, M index or m-quotient is suggested. M index weighs the period of academic endeavour to reduce the

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biasness in favour of authors with longer careers. M quotient = h- index / number of years since the first

published paper of the author. G index is a variant of h-index which considers the evolution of the most cited

papers over time. It is the largest number or rank ‘g’ of the paper after arranging all the papers of the concerned

author in descending order of citations at which first g papers together have at least g

citations. G index always

exists for any set of papers and is unique in nature.

Table 6 shows the Author’s impact of top 10 Articles. Bouri E. is at the first position with highest numbers in

all the parameters i.e., indices, citation and number of publications. He started his publication in this field in

2017 with the productivity of 8 documents per year.

Figure 6 – Most relevant affiliations (according to authors)

Figure 6 shows the top 10 affiliations i.e., related institutions, universities or any other organisations, out of

1270. The picture shows the total production of all the authors related to the affiliations. These 10 affiliations

have 336 articles which constitutes one fourth of the total articles of 1344. University of Economics Ho Chi

Minh City is at the top of the list with the maximum production of 60 articles i.e., 4.46% of the total. It has

started it production just three years ago in 2019 in this field and with its continuously increasing production; it

has reached at the top of the list. Other organizations performing well in the field are Montpellier Business

School, France, Trinity College, Dublin etc.

Countries’ Scientific Production

Table 7

Region

Frequency

CHINA

568

USA

375

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294

FRANCE

160

GERMANY

118

AUSTRALIA

114

VIETNAM

103

SPAIN

100

IRELAND

TURKEY

Table 7 shows the top 10 countries in terms of scientific production. China is positioned at the top with 568

articles and USA is following it with 375 articles. From the countries given in the table Australia has started its

publication in 2014 ahead of all other countries. China’s scientific production in the field started in 2016, which

is relatively later than that of many others. But its active involvement mainly from 2020, made it to reach to the

top of the list.

Corresponding Author is the author which acts as the contact person for the publication house for any

information or other work regarding the document for which he is designated as corresponding author. He is

treated very important for the document. One reason behind it is that first author which is the largest contributor

to the document, is designated as corresponding author.

Table 8 displays top ten countries in terms of articles related to the corresponding authors of that country. In this

list too, China is at the top of the list with 236 articles which constitutes 17.6% of the total production. In these

articles 150 are wholly produced by China and 86 articles have contributions of other countries’ authors too. It

also shows its good collaboration with other countries in terms of scientific production in this area. USA and

UK hold second and third positions in both the list of countries’ scientific production in terms of total articles

as well as corresponding author’s country.

Corresponding Author’s Country

Table 8

Country

Articles

SCP

MCP

%age

MCP_Ratio

CHINA

236

150

17.6

0.364

USA

168

120

12.5

0.286

UNITED

KINGDOM

133

9.9

0.474

AUSTRALIA

3.9

0.385

FRANCE

3.8

0.627

GERMANY

3.6

0.449

SPAIN

3.6

0.396

KOREA

3.1

0.439

IRELAND

2.8

0.868

ITALY

2.3

0.387

*SCP- Single Country Production, MCP- Multiple Country Production

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Most Global Cited Documents

Figure 7 – Top ten Global cited documents

Figure 7 displays the top ten most global cited documents. It means the documents which have been referred the

most by any other documents in the whole Database. The document DYHRBERG AH, 2016, FINANC RES

LETT-a is at the top of the list with 565 citations. The title of the document is “Bitcoin, gold and the dollar – A

GARCH volatility analysis”. This paper has explored the financial capabilities of Bitcoin using GARCH models.

It has evaluated the relationship of Bitcoin with gold and Dollar and has shown how Bitcoin can be used in risk

management by the investors. Second and the third position are occupied by BOHME R, 2015, J ECON

PERSPECT and Urquhart A, 2016, Econ Lett. Former has explained the Bitcoin in terms of its technology,

Economic implications and its governance throughout the globe, while the later has tested the efficiency of

Bitcoin.

Most Frequent Words (Tree Map)

Figure 8- Tree Map of most frequent Words

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Tree map is a method of visual representation displaying pecking order of data by using nested rectangles to

represent the branches of a tree diagram. Each rectangle has an area proportional to the amount of data it

represents. Different Colours are used to differentiate each data set. Fig. 8 represents the Tree Map of most

frequent words of author’s keyword filed. Map shows Bitcoin as the most frequent words among all the author’s

keywords. But Cryptocurrency and Cryptocurrencies which represent the same thing jointly represent the

maximum frequency of 26% which is larger than that of Bitcoin. So practically speaking Cryptocurrency (along

with its variant Cryptocurrencies) is the most frequent words followed by Bitcoin and blockchain.

Figure 9- Word Dynamics

Word dynamics shows the progression of the word uses according to the time. Fig.9 shows the word dynamics

of top ten most frequent words. It is clearly evident that the Bitcoin has earliest presence in the articles even

before the word Cryptocurrency or Cryptocurrencies that started to appear from the year 2015 a year after than

that of Bitcoin.

This shows the popularity of Cryptocurrency and its importance in the spread of Cryptocurrency. Words like

Gold, volatility, safe haven, market efficiency, started to appear in the articles from 2015 and 2016 and have

continuously increasing trends, which shows the interest of the academician towards the idea of Cryptocurrency

as a financial asset and an investment option.

Words like Blockchain and Fintech have their appearance a little bit later from 2017, that was the time of

increasing acceptance of Blockchain as a financial technology by many large companies. All these lead to adopt

Cryptocurrency as an investment option by the investors, which is evident from the Cryptocurrency boom/ hike

of 2017.

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Co-authorship

Figure 10- Overlay Visualization of Co-authorship - authors

Co-authorship means writing an article jointly by two or more authors. It can be analysed taking author,

organisation and country as unit of analysis. Fig.10 shows the overlay visualization of Co-authorship by taking

Authors as unit of analysis and Link Strength as weight. It shows that Elie Bouri, has the largest circular label,

which shows that he has the highest link strength among all i.e. he has maximum number of documents authored

with other authors. It is also clear from the colour of the bubble that most of his publications are around the year

2020. But he has also collaborations with some newer authors in the field, like xu, yahua. Bouri, ellie is followed

by Corbett, shaen and roubaud, david. Roubaud, david who has maximum publications around 2019 is closely

related to bouri, ellie because both are within the same cluster and labelled very closely.

Figure 11- Overlay visualization of Co-authorship – Organisations

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Fig.11 displays the co-authorship taking organisation as the unit of analysis. It shows the organisation’s

collaboration through its authors for writing different documents. University of economics, Ho chi minh city is

showing the highest co-authorship link strength with the highest 42 documents. Trinity college, Dublin and

Montpellier business school, France are following university of Economics, Ho Chi Minh City. Trinity college,

Dublin and university of economics Ho chi minh city have most of the documents of around 2021 but

Montpellier business school, France has of around 2019. All these top three organisations have also good mutual

co-authorship collaboration

Figure 12- Overlay visualization of co-authorship – countries

Fig.12 shows co-authorship overlay visualization taking country as the unit of analysis. This shows the link

among the countries for writing documents jointly by the authors of the countries. England has the maximum

co-authorship link strength with 200 documents which is lower than its follower Peoples republic china. France

is at 3

position. All three have average publication year of approximately 2020 but china has a little bit higher

average publication year. Iceland which has average publication year of 2022 shows that it is very active in the

recent years.

Co-occurrence of Keywords

–

Figure 13- Overlay visualization of co-occurrence of keywords

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Co-occurrence of keywords indicates the frequency of occurrence a word together with other words. Fig.13

presents the overlay visualization of co-occurrence of Author’s keywords taking total link strength as the weight.

Author’s keywords are the words used in the documents and indicated by the authors as important and key to

understand the paper.

Author’s keywords are selected for the visualization because these are really the important words because these

are selected by the authors who have written the documents and know much better than any other about their

articles. In the figure the software has displayed Bitcoin having maximum link strength for co-occurrence among

all. After that Cryptocurrency/Cryptocurrencies (can be treated as one because both represent almost same thing)

and Blockchain are positioned.

All these three top co-occurring words have average year of publication around 2020. Carbon emission, leverage

effect, stable coin, analytical models, decentralized finance etc. are words co-occurring with these top occurring

words in recent years. Also, these top keywords have co-occurrence with most of the other words.

Bibliographic coupling –document

Figure 14- Overlay visualization of Bibliographic coupling of documents

Bibliographic coupling means the occurrence of the same reference in the bibliography or references of two

documents. For the unit of analysis documents, sources, authors, organizations and countries can be considered.

Fig.14 presents the overlay visualization of bibliographic coupling taking documents as the unit of analysis. The

plots are drawn taking total link strength as weight.

This visualization shows that bariviera (2021a). Flori (2019) and bedi (2020) are the top three documents which

have maximum total link strength which show these are the most influential documents in terms of bibliographic

coupling.

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Figure 15- Overlay visualization of Bibliographic coupling of sources

Fig.15 shows the bibliographic coupling visualization taking sources as the unit of analysis. It shows the

documents related to sources which are cited commonly by two documents and their frequency with weight in

the form of total link strength. Finance research letters has the maximum total link strength which implies that

its documents have maximum common bibliographic presence in two documents. Research in international

business and finance and international review of financial analysis are the 2

and 3

in terms of total link

strength for bibliographic coupling. All these sources have average year of publication is around 2020.5. This

shows the presence of their maximum documents of around mid-2020.

Co-citation

Figure 16- Network diagram of co-citation of cited references

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Co-citation means the presence of citations of two different documents together in a third document. It can be

analysed taking cited references, authors and sources as the unit of analysis. Fig.16 shows the network

visualization of co-citation taking cited references as the unit of analysis. Reference “corbet s, 2018, econ lett,

v165, p28, doi 10.1016/j.econlet.2018.01.004” has maximum total link strength. This shows its maximum

presence in pair with some other documents in the reference of the documents. There are seven clusters displayed

by the software. This most influential cited reference is in second largest cluster2 with other 241 documents.

Figure 17- Network diagram of co-citation of authors

Fig.17 shows the network visualization of co-citation analysis with author as unit of analysis. It shows that Elie

Bouri has the maximum total link strength followed by corbet,s and baur,dg. Top 1000 authors are classified

into five clusters according to the similarity of their works.

Figure 18- Network diagram of co-citation of sources

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Fig.18 displays co-citation analysis of sources. According to this Finance research letters has maximum total

link strength along with the maximum citations. Economic letters and international review of financial analysis

are at the second and the third positions in terms of total link strength. This shows the articles of these sources

have maximum presence in the bibliography of the documents coupled with other documents. Top 1000 most

influential sources according to the co-citation link strength are classified into five clusters. All the top three

sources are among the top three clusters which contain maximum number of sources.

CONCLUSION

Our analysis shows that there were early trials of Cryptocurrencies before the inception of Bitcoin. But after the

emergence of Bitcoin in 2008, the concept got solidified and appealing. The first document in this area appeared

in 2011 in Forbes. There is a continuous increase in the literature, mainly in the last five years. A very high

annual growth rate of documents of 68.16% is observed. Most of the works are done related to Bitcoin. Finance

Research Letters is the most impactful source. It has the highest local and global citations. China is the leader in

scientific production in the field, despite obstructive actions by the Chinese government. University of

Economics Ho Chi Minh City has emerged as the most relevant affiliation with the highest number of

documents. The number of countries participating in this field is increasing, but the contribution of many of

them is very insignificant. The detailed insights of the study will be helpful for academicians and researchers in

finding out about cryptocurrency and the related areas that are investigated, and in deciding which area to focus

on for further studies.

This study is delimited to the data available in the Web of Science database only. So, further research can be

done by considering the other databases like Scopus, Google Scholar, etc., individually or in a combined form.

As this study has reflected, most of the research revolves around bitcoin, blockchain, market efficiency, cyber

fraud hedging, etc., and there are some areas that are unexplored or very little explored. So, future research can

delve into those less studied areas like return spillover, pricing efficiency, market integration, sustainability,

blockchain governance, etc.

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