=Paper=
{{Paper
|id=Vol-3282/icaiw_aiesd_8
|storemode=property
|title=Retrospective of Scientific Production on e-Democracy
|pdfUrl=https://ceur-ws.org/Vol-3282/icaiw_aiesd_8.pdf
|volume=Vol-3282
|authors=Alejandra Colina Vargas,Marcos Espinoza-Mina
|dblpUrl=https://dblp.org/rec/conf/icai2/VargasE22
}}
==Retrospective of Scientific Production on e-Democracy==
https://ceur-ws.org/Vol-3282/icaiw_aiesd_8.pdf
Retrospective of Scientific Production on
e-Democracy
Alejandra Colina Vargas, Marcos Espinoza-Mina*
Universidad Ecotec, Samborondón, Ecuador
Abstract
E-democracy refers to the use of information technologies in a political system, which facilitates the
exchange of information and the articulation of interests between social and political actors in a democ-
racy. This concept is on the rise, and its incidence and impact is of great interest to researchers around
the world. Therefore, it is necessary to elaborate a general and structural mapping that helps researchers
to understand certain political-social phenomena that occur in contemporary times. The objective of this
study was to carry out a bibliometric analysis of the scientific production around the term e-democracy.
Methodologically, the research was conducted through the phases of a bibliometric study whose data
sources were WoS and Scopus, extracting 311 and 468 articles, respectively. Among the main results,
it was found the evolution of research with a growth of less than 5%, with no defined trend and a
low international collaboration. United Kingdom stands out as the country with the highest scientific
production in both databases consulted. "Coleman S." emerges as the most cited author among the
extracted documents. The first institution is the University of Granada.
Keywords
Bibliometrics, Policy, Citizen Participation, Democracy
1. Introduction
E-democracy focuses on the use of information technology (IT) to improve democracy [1].
E-democracy is considered as an approach to improve the quality of citizen participation in
democratic processes [2]. IT offers opportunities for greater citizen participation in democratic
reform. However, they have only been associated with e-government applications, which focus
on one-way information provision and service delivery. In contrast, e-democracy processes
facilitate active civic engagement through continuous two-way dialogue [3].
Today, country leaders are making more active use of e-democracy tools to interact with
community members on the basis of government transparency and openness [4]. The use of
IT in social and political issues is increasing, and the study of its impact is being analyzed by
researchers around the world.
In [5] evaluated the introduction of online tools in candidate selection processes in German
political parties. They found that support or opposition to the use of technology does not
ICAIW 2022: Workshops at the 5th International Conference on Applied Informatics 2022, October 27–29, 2022, Arequipa,
Peru
*
Corresponding author
$ acolina@ecotec.edu.ec (A. Colina Vargas); mespinoza@ecotec.edu.ec (M. Espinoza-Mina)
0000-0003-1514-8852 (A. Colina Vargas); 0000-0003-1530-7243 (M. Espinoza-Mina)
© 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR
Workshop
Proceedings
http://ceur-ws.org
ISSN 1613-0073
CEUR Workshop Proceedings (CEUR-WS.org)
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Alejandra Colina Vargas et al. CEUR Workshop Proceedings 138–158
depend on a generational difference, but on how power and influence are distributed within the
political party and how participants conceive this inclusion. In [6] quantified the communicative
behavior of politicians using more than 366000 tweets posted by more than 1000 prominent
German politicians in the 2017 election year. They presented how different political parties
engage to a greater or lesser extent with prominent topics, and how their strategies evolve in
the run-up to elections.
Collecting, synthesizing, and analyzing scientific evidence on a topic is very important. The
bibliographic method is considered fundamental for mapping the state of the object of study,
consolidating the heterogeneous body of public relations knowledge, and pointing out potential
new directions of a research topic [7]. Moving up to the bibliometric method can facilitate
the understanding of a topic when trying to locate scientific gaps or mapping where one is,
or wants to be, in the field of scientific discourse [8]. Bibliometrics is useful for the in-depth
analysis of aspects related to quality scientific production. Sources, authors or countries can be
evaluated, providing relevant information for decision-making. For example, an overview of
the main trends of a journal can be obtained [9].
The present study used bibliometric methods to provide information on high-impact scientific
production related to e-democracy. Data were extracted from two of today’s most prominent
scientific information databases. In addition, tools with statistical analysis and bibliometric
network visualization approaches were employed.
2. Methodology
In order to present the most relevant information on the scientific production related to e-
democracy, activities grouped in three stages were developed; some of them are described
below.
In the first stage, "data collection", the Web of Science (WoS) and Scopus databases were used
to extract data on scientific production related to e-democracy. Scientific articles in the English
language were taken, from 2002 to June 2022.
For the second stage, "bibliometric analysis and visualization", the collected data were pro-
cessed to generate relevant information using the R programming language, through the RStudio
integrated development environment, and the Bibliometrix package [10]. Bibliometrix can be
used as part of a broader, more general data analysis workflow [11]. RStudio and Biblimetrix
allowed the processing of the extracted data. Detailed statistical information was obtained
through variables, tables, and graphs.
With VOSviewer 1.6.18 software, knowledge graphs were constructed from data extracted
from Scopus and WoS. This tool was developed by Nees Jan van Eck and Ludo Waltman of
Leiden University in the Netherlands to map and visualize econometric networks [12]. To
improve the results of the maps, the author and subject thesaurus, integrated into the same
software, were applied in some cases. In addition, the "full counting" weight assignment method
was used in all analyses [13]. This resulted in the identification of the most representative items,
which show the largest size in the circle and its label. From this, it is interpreted in the graphs,
that the most representative items have more linking strength in the knowledge structure for
each analysis unit.
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With the variables, tables, and knowledge maps based on data texts, taking the topics from
the titles and fields of the summary, the third and last stage "conclusions" began.
3. Results
3.1. Chronology of scientific production
From 2002 to July 2022, 311 articles were evaluated in WoS and 468 in Scopus. The total annual
production recorded in both databases is variant, and there is no trend (see Figure 1). The
growth rates were low, 4.89% for WoS and 3.53% for Scopus. Despite the difference in the totals
for the period evaluated, in the last three years, the annual totals tend to coincide.
Figure 1: Chronology of research by total articles.
3.2. Countries with outstanding scientific production
When evaluating the ten countries with the highest scientific production, they coincide in both
databases: United Kingdom, USA, Italy, Spain, Australia, Sweden, and the Netherlands. Of
the countries referred to, all have very low international collaboration; that is, they have an
inter-country index below 0.50, see Table 1. These countries have strong national collaboration.
When evaluating the ten countries with the highest number of citations of their scientific
production, in the case of WoS, Italy, Ukraine and Germany disappear; Canada, Austria, and
Denmark appear. In Scopus, Greece disappears and China appears. See Table 2.
Table 3 contains some of the first titles extracted from the databases, which served as a
recognition of the topics dealt with in the scientific productions related to e-democracy. They
highlight themes such as the use of government websites; people’s participation in political
actions; digital communication; populism and technology; misuse of technology in politics;
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Table 1
Top ten countries by number of articles
WoS Scopus
A B C D E F A B C D E F
UNITED UNITED
42 0.1364 33 9 0.214 56 0.1662 45 11 0.196
KINGDOM KINGDOM
USA 36 0.1169 32 4 0.111 USA 43 0.1276 39 4 0.093
ITALY 19 0.0617 13 6 0.316 ITALY 22 0.0653 16 6 0.273
SPAIN 18 0.0584 14 4 0.222 SPAIN 22 0.0653 18 4 0.182
AUSTRALIA 17 0.0552 12 5 0.294 GREECE 19 0.0564 17 2 0.105
SWEDEN 13 0.0422 11 2 0.154 AUSTRALIA 16 0.0475 12 4 0.250
CHINA 11 0.0357 8 3 0.273 SWEDEN 15 0.0445 12 3 0.200
UKRAINE 10 0.0325 10 0 0.000 NETHERLANDS 11 0.0326 9 2 0.182
GERMANY 9 0.0292 9 0 0 .000 CANADA 10 0.0297 7 3 0.300
NETHERLANDS 9 0.0292 6 3 0.333 AUSTRIA 9 0.0267 8 1 0.111
(A) Country (B) Articles (C) Frequency (D) Intra-country collaboration index (E) Inter-country
collaboration index (F) Inter-country relationship.
Table 2
Top ten countries by number of citations
WoS Scopus
Average Article Average Article
Country Total Citations Country Total Citations
Citations Citations
USA 1441 40.028 UNITED KINGDOM 1792 32.00
UNITED KINGDOM 1331 31.690 USA 1347 31.33
SPAIN 697 38.722 SWEDEN 634 42.27
CHINA 509 46.273 CANADA 620 62.00
SWEDEN 493 37.923 SPAIN 498 22.64
CANADA 407 58.143 CHINA 305 61.00
AUSTRALIA 357 21.000 AUSTRALIA 295 18.44
AUSTRIA 191 38.200 ITALY 290 13.18
NETHERLANDS 155 17.222 NETHERLANDS 210 19.09
DENMARK 128 128.000 AUSTRIA 186 20.67
evaluation of IT integration in democracy; electronic voting; IT to achieve transparency; citizens’
acceptance of IT in democratic processes; social networks; the attack on privacy through bigdata
in politics; political parties and IT; political disinformation in social networks; electronic data
for public decision-making; IT risks in politics; IT as a means of innovation in the public sector
and inclusive processes.
Table 3
Featured country research in WoS and Scopus
Country Title Ref.
UNITED KINGDOM Digital Communication and Representational Interactivity: [14]
an Analysis of www.WriteToThem.com in Scotland
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USA E-Democracy, E-Commerce, and E-Research: Examining [15]
the Electronic Ties Between Citizens and Governments
ITALY A role-based mobile-agent approach to support e- [16]
democracy
SWEDEN Technology and democracy: validity in measurements of [17]
e-democracy
ITALY E-Democracy and Digital Activism: From Divergent Paths [18]
Toward a New Frame
ITALY Populisms among technology, e-democracy and the de- [19]
politicisation process
USA The Problem of Citizens: E-Democracy for Actually Exist- [20]
ing Democracy
UNITED KINGDOM Deliberative Manoeuvres in the Digital Darkness: E- [21]
Democracy Policy in the UK
AUSTRALIA Letting the public in: dialectic tensions when local govern- [22]
ments move beyond e-government to e-democracy
UNITED KINGDOM Bringing E-Democracy Back In: Why it Matters for Future [23]
Research on E-Governance
UNITED KINGDOM Cybernetics and e-democracy [24]
USA E-democracy@China: does it work? [25]
UNITED KINGDOM Web-enabled strategic GDSS, e-democracy and Arrow’s [26]
theorem: A Bayesian perspective
SWEDEN A Knowledge Perspective on e-Democracy [27]
UNITED KINGDOM The Scottish Parliament and e-democracy [28]
UNITED KINGDOM Developing local e-democracy in Bristol: From information [29]
to consultation to participation and beyond
SPAIN; USA E-DEMOCRACY WRIT SMALL: The impact of the Internet [30]
on citizen access to local elected officials
UNITED KINGDOM e-Voting: Powerful Symbol of e-Democracy [31]
SPAIN A Group Decision-Making Methodology with Incomplete [32]
Individual Beliefs Applied to e-Democracy
CHINA;USA Testing the Development and Diffusion of E-Government [33]
and E-Democracy: A Global Perspective
UNITED KINGDOM ‘Mind the Gap’: e-Government and e-Democracy [34]
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CHINA Enhancing e-Democracy Via Fiscal Transparency: A Dis- [35]
cussion Based on China’s Experience
ITALY; SPAIN Financial Sustainability as a Driver for Transparency and [36]
E-Democracy: A Comparative Study in Italian and Spanish
Local Governments
KOREA; USA Will the internet promote democracy? search engines, [37]
concentration of online news readership, and e-democracy
UNITED KINGDOM Local Democracy Shaping e-Democracy [38]
NIGERIA; USA Empirical study of user acceptance of online political partic- [39]
ipation: Integrating Civic Voluntarism Model and Theory
of Reasoned Action
UNITED KINGDOM Electronic Democracy and Young People [40]
ITALY No (e-)Democracy Without (e-)Knowledge [41]
USA Examining Development of E-Government in Russia and [42]
China: A Comparative Approach
SWEDEN Emerging Electronic Infrastructures: Exploring Demo- [43]
cratic Components
ITALY A protocol for anonymous short communications in social [44]
networks and its application to proximity-based services
GREECE Big data analytics in e-government and e-democracy ap- [45]
plications: privacy threats, implications and mitigation
USA Digital Governance: An Assessment of Performance and [46]
Best Practices
UNITED KINGDOM;
Learning VAA: A new method for matching users to parties [47]
USA
in voting advice applications
SPAIN Disinformation, social media, bots, and astroturfing: the [48]
fourth wave of digital democracy
USA Does Domestic Political Instability Foster Terrorism? [49]
Global Evidence from the Arab Spring Era (2011–14)
SPAIN;USA E-Voting System Evaluation Based on The Council of Eu- [50]
rope Recommendations: Helios Voting
USA Voting is a right: a decade of societal, technological and [51]
experiential progress towards the goal of remote-access
voting
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GREECE; IRELAND;
A study of higher education students’ self-perceived dig- [52]
UNITED KINGDOM
ital competencies for learning and everyday life online
participation
USA Assessing e-government capacity to increase voter partici- [53]
pation: Evidence from the U.S.
CHINA; SAUDI ARA-
BIA; SPAIN; UNITED Large-Scale decision-making: Characterization, taxonomy, [54]
KINGDOM challenges and future directions from an Artificial Intelli-
gence and applications perspective
USA A Cross-National Analysis of Lifespan Inequality, [55]
1950–2015: Examining the Distribution of Mortality
Within Countries
USA A Systematic Review of Multiple Terminologies for ICT [56]
in Government: A Mesh of Concentric and Overlapping
Circles
ITALY; USA Reply structure and participation in online conversations [57]
enabled by argumentation platforms: A real-world experi-
ment of collective deliberation in e-democracy
BELGIUM; FRANCE;
SPAIN; UNITED KING- Power users in online democracy: their origins and impact [58]
DOM
SWEDEN Electronic government: Towards e-democracy or democ- [59]
racy at risk?
GREECE E-Governance in educational settings: Greek educational [60]
organizations leadership’s perspectives towards social me-
dia usage for participatory decision-making
CHINA; SPAIN;
Dealing with incomplete information in linguistic group [61]
UNITED KINGDOM
decision making by means of Interval Type-2 Fuzzy Sets
FRANCE; SAUDI ARA-
BIA; SPAIN; UNITED A social network based approach for consensus achieve- [62]
KINGDOM ment in multiperson decision making
ITALY From Smart-Cities to Smart-Communities: How Can We [63]
Evaluate the Impacts of Innovation and Inclusive Processes
in Urban Context?
CHINA; SPAIN;
A review on trust propagation and opinion dynamics in [64]
UNITED KINGDOM
social networks and group decision making frameworks
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PORTUGAL; SPAIN Citizens’ intention to use and recommend e-participation: [65]
Drawing upon UTAUT and citizen empowerment
USA Harnessing the power of mobile technology to bridge the [66]
digital divide: a look at U.S. cities’ mobile government
capability
CHINA; SPAIN;
A novel consensus model for multi-attribute large-scale [67]
UNITED KINGDOM
group decision making based on comprehensive behavior
classification and adaptive weight updating
UNITED KINGDOM Seeking Evidence for a Welsh Progressive Consensus: Party [68]
Positioning in the 2016 National Assembly for Wales Elec-
tion
USA When Does Public Participation Make a Difference? Evi- [69]
dence From Iceland’s Crowdsourced Constitution: Public
Participation in Constitution Drafting in Iceland
ITALY Mobilizing young voters? A cross-national analysis of [70]
contextual factors in pirate voting
3.3. Institutions with the greatest scientific production
A total of 385 different institutions (affiliations) were identified in WoS and 494 in Scopus. Table
4 shows the 10 institutions with the highest number of articles for both WoS and Scopus. The
count was made depending on the registered institution of each of the authors involved in
scientific production.
Table 4
Top ten institutions by number of articles
WoS Scopus
A B C A B C
UNIV GRANADA 13 0.015662651 UNIVERSITY OF GRANADA 10 0.013966480
UNIV OREBRO 13 0.015662651 UNIVERSITY OF MANCHESTER 9 0.012569832
UNIV ZARAGOZA 12 0.014457831 ÖREBRO UNIVERSITY 8 0.011173184
NAPIER UNIV 11 0.013253012 DE MONTFORT UNIVERSITY 7 0.009776536
UNIV OXFORD 10 0.012048193 UNIVERSITY AT ALBANY 7 0.009776536
UNIV TECHNOL SYDNEY 9 0.010843373 UNIVERSIDAD DE ZARAGOZA 6 0.008379888
DE MONTFORT UNIV 8 0.009638554 UNIVERSITY OF LEEDS 6 0.008379888
UNIV TEHRAN 8 0.009638554 UNIVERSITY OF OXFORD 6 0.008379888
GERMAN UNIV ADM SCI SPEYER 7 0.008433735 ERASMUS UNIVERSITY ROTTERDAM 5 0.006983240
UNIV UTRECHT 7 0.008433735 IONIAN UNIVERSITY 5 0.006983240
(A) Affiliations (B) Number of articles (C) Proportion.
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3.4. Sources with the greatest scientific production
Figure 2 shows the top ten sources (journals) by the number of articles in each of the databases
evaluated. From these lists, the presence in both databases of the journals "Information Com-
munication and Society", "Government Information Quarterly" and "Journal of Information
Technology and Politics" stands out. They are accompanied by "Electronic Government Pro-
ceedings" and "E-journal of E-democracy and Open Government".
Figure 2: Top ten sources by the number of articles.
3.5. Bradford’s Law
Bradford’s law states that for a subject area there are few but very productive journals, a larger
number of regular producers, and a much larger number with very low productivity. Applying
Bradford’s law to WoS records, there are 13 sources with 103 articles in the first group, and in the
third group, 176 journals are linked to only 311 articles. In the case of Scopus, the concentration
is stronger, 10 sources have 158 articles. The three zones according to Bradford’s law are shown
in Table 5.
From the list of the top five journals with the most publications on e-democracy in WoS and
Scopus (see Table 6); as defined by Bradford’s law, most of the publications are concentrated in
Table 5
Division of sources according to Bradford’s law zones: WoS and Scopus
WoS Scopus
A B C D E F B C D E F
1 13 7 103 33.12 7.92 10 5 158 33.76 15.80
2 61 35 106 34.08 1.74 62 27 156 33.33 2.51
3 102 58 102 32.80 1 154 68 154 32.91 1
- 176 100 311 100 - 226 100 468 100 -
(A) Zone (B) Sources (C) Percentage sources (D) Articles (E) Article percentage (F) Average articles per source
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Table 6
Top five magazines belonging to zone one according to Bradford’s law: WoS and Scopus
Data Base A B C D E
INFORMATION COMMUNICATION & SOCIETY 21 21 0,067524116 0,067524116
GOVERNMENT INFORMATION QUARTERLY 16 37 0,051446945 0,118971061
WoS ELECTRONIC GOVERNMENT, PROCEEDINGS 12 49 0,038585209 0,157556270
GROUP DECISION AND NEGOTIATION 8 57 0,025723473 0,183279743
ELECTRONIC GOVERNMENT, PROCEEDINGS 7 64 0,022508039 0,205787781
INTERNATIONAL JOURNAL OF ELECTRONIC GOV-
23 23 0,049145299 0,049145299
ERNANCE
INFORMATION COMMUNICATION AND SOCIETY 22 45 0,047008547 0,096153846
Scopus
EJOURNAL OF EDEMOCRACY AND OPEN GOV-
20 65 0,042735043 0,138888889
ERNMENT
INFORMATION POLITY 16 81 0,034188034 0,173076923
JOURNAL OF INFORMATION TECHNOLOGY AND
16 97 0,034188034 0,207264957
POLITICS
(A) Source (B) Frequency, (C) Accumulated frequency (D) Percentage of frequency (E) Percentage of accumulated frequency
these first journals.
3.6. Lotka’s Law
Lotka’s law is a discrete probability distribution function. Under this law author productivity
is characterized. This law states that a large proportion of scientific output is produced by a
small number of authors. It states that the number of authors producing ’n’ scientific papers is
approximately proportional to 𝑛12 .
Table 7
Observed and theoretical distribution of scientific productivity: Lotka law
Data Base A B C D E
1 532 0.897133221 532 1.01399724
2 47 0.079258010 94 0.25349931
WoS 3 10 0.016863406 30 0.11266636
4 3 0.005059022 12 0.06337483
5 1 0.001686341 5 0.04055989
1 742 0.881235154 742 0.86525757
2 65 0.077197150 130 0.21631439
Scopus 3 21 0.024940618 63 0.09613973
4 10 0.011876485 40 0.05407860
5 1 0.001187648 5 0.03461030
6 1 0.001187648 6 0.02403493
7 1 0.001187648 7 0.01765832
8 1 0.001187648 8 0.01351965
(A) Number of articles (B) Number of authors (C) Frequency (Observed Distribution)
(D) Author appearances (E) Theoretical Distribution
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Figure 3: Observed and theoretical distribution (Lotka’s law)
Table 7 shows the calculations of the observed and theoretical discrete productivity distribu-
tion. For WoS the beta coefficient was 3.857445, the constant 1.013997 and the goodness of fit
to the normal distribution was 0.9963046. For Scopus, the value of 3.451103 was calculated for
the beta coefficient, 0.8652576 for the constant, and goodness of fit of 0.9558415 was obtained.
The two-sample Kolmogorov-Smirnoff test provided a p-value of 0.3291164 for WoS and
0.08786641 for Scopus. There is no significant difference between the observed and theoretical
distributions, see Figure 3.
3.7. Analysis by co-citations
Co-citation analysis is a measure of the relationship between authors or sources, taking as a
reference the use of direct citations, through the frequency in which two documents, jointly,
cite a third publication [71].
Co-citation analysis was obtained using the VOSviewer tool. Co-citation analysis by cited
authors was obtained by calculating the total number of occurrences of a citation in all papers.
The results reflect those authors who have influenced the active authors (see Figure 4), being
the case for WoS and Scopus of "Coleman, S." with 91 and 227 citations, respectively.
(a) WoS (b) Scopus
Figure 4: Visualization of author co-citation analysis.
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(a) WoS (b) Scopus
Figure 5: Visualization of co-citation analysis of sources.
Co-citation at the source level reveals within its results, the influence that a source has on the
scientific community, evidenced through citations. This is the case for both WoS and Scopus,
the source "Government Information Quarterly", with 425 and 390 citations, respectively. This
result reflects the influence of this source on the scientific community in relation to e-democracy
(see Figure 5).
3.8. Co-Authorship Analysis
In the co-authorship analysis, the size of the circles represents the author link weights, and
the color of the gradient is the mean citation scores of the articles. For the identification of the
cooperation patterns of authors and organizations, whose research is related to e-democracy,
the coauthorship visualization function was used. Figure 6 shows the cooperation network of
authors in the research community.
In the identification of the data by author, based on the co-authorship map, a document and
a citation were established per author as eligibility criteria, in order to find the most prominent
documents (WoS with 609, and Scopus with 842) that had published on e-democracy. In the
resulting networks, 501 authors are related in WoS and 729 in Scopus; 17 items from WoS and
16 from Scopus were considered in the analysis. In WoS and Scopus, the author "Palomares
Ivan" stands out as one of the most outstanding authors in terms of cooperation, with a value
of 13, in the total strength of the link.
As for the co-authorship maps, whose unit of analysis was the cooperation of the organiza-
tions, the minimum values of choice for an organization were defined as having a document
and a citation, in order to identify the most visible organization (WoS with 387, and Scopus
with 737), with research on the topic of e-democracy. There are 323 organizations linked in the
resulting networks in WoS and 647 in Scopus; 19 items in WoS and 10 in Scopus were considered
in the analysis; see Figure 7.
In WoS, it was obtained as a result that the organization that stands out the most is the
University of Granada with 22 cooperation link strengths; on the other hand, the results in
Scopus show eight institutions with a value of 8 in the cooperation link strength, they are:
University of Granada (Andalusian Research Institute On Data Science And Computational
Intelligence), Sichuan University (Business School), Tianjin University (College of Management
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and Economics), King Abdulaziz University (Department of Electrical and Computer Engineer-
ing), King Abdulaziz University (Faculty of Computing and Information Technology), University
of Russia (Peoples’ Friendship), Southwestern University of Finance and Economics (School of
Business Administration), University of Bristol (School of Computer Science), Beijing Institute
Of Technology (School of Management and Economics), Chongqing University (School of Public
Affairs), The Alan Turing Institute.
3.9. Analysis by author
Figure 8 shows each author as a unit of analysis with a circle (node) and a label, where the
size is associated with the total link strength of the most cited researchers. In the case of WoS,
"Bingham, Lb.", "Nabatchi, T." and "O’Leary, R." with 478 citations and 683 as the relationship
index. On the other hand, in Scopus, "Wright S." and "Palomares I." obtained 657 and 442 citations,
with a ratio strength of 1446 and 1628, respectively.
It is highlighted in this analysis that the closer the nodes are in the visualization, the greater
the relationship between them. This is the case of researchers who are located very close to each
other; this is because they are citing the same authors in their production; an example are the
researchers "Bingham, Lb.", "Nabatchi, T." and "O’Leary, R.". In the analysis of the colors, clusters
of researchers emerge with a high level of relationship of bibliographic coupling strength of
authors with each other, highlighting 21 clusters for WoS and 35 for Scopus.
3.10. Country analysis
In the AAB by country, the maximum number of countries per document was defined as 25; the
minimum number of documents from a country and the minimum number of citations from
a country was 1. The result for WoS data was 62 countries and for Scopus 83; of which 58 in
WoS and 76 in Scopus are within the limit to be calculated in the total AAB ratio, which was
equivalent to 93.54% in WoS and 91.56% in Scopus.
(a) WoS (b) Scopus
Figure 6: Visualization of the analysis of co-authors by author.
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(a) WoS (b) Scopus
Figure 7: Visualization of the analysis of co-authors by institution.
(a) WoS (b) Scopus
Figure 8: Visualization of the analysis by the author.
3.11. Analysis by sources
In the analysis carried out for the recognition of the main sources in citations, the AAB was
used, whose unit of analysis considered as the source (see Figure 9); this occurs when two
sources are cited in common by a third [72]. The strength of the coupling between sources
is determined by the frequency of common citations. In WoS, the sources with the highest
frequency of citations are "Public Administration Review" and "New Media & Society", with
732 and 651 citations, respectively. In Scopus, "A New Media and Society" stands out with 796
citations, and "Information Communication and Society" with 746.
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(a) WoS (b) Scopus
Figure 9: Visualization of the analysis by source.
Table 8
Top 10 terms from WoS and Scopus data theme analysis
WoS Scopus
Terms Occurrences Terms Occurrences Terms Occurrences Terms Occurrences
E-Democracy 248 Participation 180 E-Democracy 420 Study 246
Study 219 Analysis 178 Democracy 293 System 225
Process 188 Paper 177 Paper 292 Participation 223
Democracy 184 Research 170 Process 290 Analysis 218
Citizen 181 Government 167 Citizen 279 Government 216
3.12. Analysis of themes based on text data
For the analysis and identification of trends in themes, the map creation function was used,
based on text data. For this purpose, selection criteria were established, a minimum of 30
occurrences, the "Full counting" method for the count, and the default VOSviewer thesaurus of
topics was added. With the WoS data, a total of 6753 terms resulted; 43 were found among the
most relevant terms that are in the evaluated limit of the model. With the Scopus data, 9010
terms were identified; 84 were found for the evaluation.
The algorithm was executed, representing in a density visualization map the relationships of
terms (see Figure 10); each point on the map has a color that depends on the density of elements;
if the term is denser, it means that it has a greater number of occurrences. The selected terms
were verified, showing the top 10 (see Table 8). The densest term in the map confirms the
theoretical assumptions reviewed in this research, related to e-democracy, and the participation
of citizens in the democratic government processes that implement it.
4. Conclusions
A total of 468 articles related to e-democracy were extracted from Scopus and 311 from WoS.
The annual production, from 2002 to June 2022, in both databases, is variant and has grown at a
rate of less than 5%. There is no trend. The number of annual papers has been higher in Scopus,
although in the last five years the scientific production of WoS has almost equaled it. The top
ten countries, by the amount of production, have very low international collaboration. United
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Kingdom, USA, Italy, and Spain have the highest scientific production in both databases.
The topics covered in the scientific productions are multiple; from the use of web pages and
social networks by the government and political parties, through electronic voting, to studies
on the violation of privacy and disinformation.
The University of Granada and Örebro University is among the first institutions with the
highest scientific production, followed by the University of Zaragoza and the University of
Manchester.
Few journals concentrate on a greater number of publications, among them are "Information
Communication and Society", "Government Information Quarterly", "Journal of Information
Technology and Politics" and "E-journal of E-democracy and Open Government".
Lotka’s law is confirmed. In both databases, scientific production is produced by a small
number of authors. There is no significant difference between the observed and theoretical
distributions.
The co-citation map of cited and citing authors and sources presents, from the published
papers, a retrospective look at the most influential authors and sources in the e-democracy
research field. The author "Coleman S.", stood out as the researcher with the highest citation in
the two databases worked. In terms of sources, "Government Information Quarterly" stands
out as the most influential in WoS and Scopus. This makes it easier to know the thematic
associations between scientific papers and improves their visibility.
A map of co-authorship networks was constructed, making it possible to identify authors
and institutions that produce research in knowledge domains related to e-democracy. In the
analysis of the author cooperation network, it is revealed that from the result of the initial
extraction, less than 1% of the total in both databases make up the network, indicating that
the phenomenon of cooperation among multiple authors is not very widespread for the object
under study. Regarding the co-authorship network by institutions, there is a marked tendency
(a) WoS (b) Scopus
Figure 10: Text-based subject analysis of data.
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for the "University of Granada" to cooperate in both databases. In Scopus, there are seven other
institutions that jointly lead the cooperation networks in existing research in e-democracy.
With the bibliographic coupling function at the level of author, countries, and sources
(journals) used in documents related to e-democracy from the analyzed sample, the most
important author, countries, and journals within the thematic flow under study were identified,
which are potentially generating impact in the development of new research.
Finally, a trend analysis of terms was performed using a text mining algorithm, facilitating the
construction and visualization of a map of the co-occurrence of terms extracted from research
related to e-democracy in WoS and Scopus, showing stronger interrelationships between the
keywords used in the source documents.
Further content analysis is recommended for future research in characterizing bibliometric
analysis.
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