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1
Research Paper
JDIS
Journal of Data and
Information Science
http://www.jdis.org
https://www.degruyter.com/view/j/jdis
A Novel Metric for Assessing National
Strength in Scientific Research:
Understanding China’s Research Output in
Quantum Technology through Collaboration
Yuqi Wang, Yue Chen†, Zhiqi Wang, Kang Wang, Kai Song
WISE Lab, Institute of Science of Science and S&T management,
Dalian University of Technology, Dalian 116024, China
Abstract
Purpose: The 5th Plenary Session of the 19th Communist Party of China (CPC) Central
Committee clearly states that developing science and technology through self-reliance and
self-strengthening provides the strategic underpinning for China’s development. Based on
this background, this paper explores a metric model for assessing national scientific research
strength through collaboration on research papers.
Design/methodology/approach: We propose a novel metric model for assessing national
scientific research strength, which sets two indicators, national scientific self-reliance (SR)
and national academic contribution (CT), to reflect “self-reliance” and “self-strengthening”
respectively. Taking the research papers in quantum technology as an example, this study
analyzes the scientific research strength of various countries around the world, especially
China in quantum technology.
Findings: The results show that the research of quantum technology in China has always been
relatively independent with fewer international collaboration papers and located in a more
marginal position in cooperation networks. China’s academic contribution (CT) to global
quantum technology research is increasing and has been greater than that of the United States
in 2020. Combining the two indicators, CT and SR, China’s research strength in the quantum
field closely follows the United States, and the United States is the most powerful with high
research autonomy.
Research limitations: This paper only reflects China’s scientific research strength in quantum
technology from collaboration on research papers and doesn’t consider the segmentation of
quantum technology and the industrial upstream and downstream aspects, which need further
study.
Practical implications: The model is helpful to better understand the national scientific
research strength in a certain field from “self-reliance” and “self-strengthening”.
† Corresponding author: Yue Chen (Email: chenyuedlut@163.com).
Citation: Wang, Y.Q.,
Chen, Y., Wang, Z.Q.,
Wang, K., & Song, K.
(2022). A Novel Metric
for Assessing National
Strength in Scientific
Research: Understanding
China’s Research Output
in Quantum Technology
through Collaboration.
Journal of Data and
Information Science.
https://doi.org/10.2478/
jdis-2022-0019
Received: May 24, 2022
Revised: Aug. 20, 2022;
Sep. 16, 2022
Accepted: Sep. 19, 2022
Journal of Data and Information Science Vol. 7 No. 4, 2022
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Research Paper
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Originality/value: We propose a novel metric model to measure the national scientific
research strength from the perspective of “self-reliance” and “self-strengthening”, which
provides a solid basis for the assessment of the strength level of scientific research in countries/
regions and institutions.
Keywords National Scientific Research Strength; Academic Contribution; National
Scientific Self-reliance Index; Quantum Technology Research
1 Introduction
As recent tensions between China, the United States, and other Western nations
spill over into the realm of science, scientific and technological self-reliance takes
center stage in China’s 14th five-year plan (Mallapaty, 2021). The 5th Plenary
Session of the 19th Communist Party of China (CPC) Central Committee clearly
states that developing science and technology through self-reliance and self-
strengthening provides the strategic underpinning for China’s development. For
scientific research, “Self-reliance” emphasizes independence and controllability,
and is manifested in autonomy; “self-strengthening” is manifested in academic
contribution. To enhance national research strength, the Chinese government has
continued to increase R&D investment and support international scientific
communication in various ways, resulting in a rapid increase in the number and
share of international collaborative papers (He, 2009; Zhou & Glänzel, 2010).
Besides, globalization also facilitates China’s research development rapidly, which
benefits a lot from international collaboration. Recent studies found that China
has become the largest contributor to global research papers (Tollefson, 2018).
Meanwhile, some studies showed that more and more Chinese scholars appear as
the first author or corresponding author in academic papers (Bornmann et al., 2015;
Wang & Wang, 2017; Wang et al., 2013). There is no doubt about the rapid
development of China’s research. However, under the background of extensive
international collaboration, it is not sufficient to assess the national research strength
only through the number of papers or citation frequency. Similar to artificial
intelligence technology, quantum technology is a kind of disruptive technology
highly valued by governments all over the world. China has more papers published
than the United States since 2013, and in 2020, the number of papers from China
is 40,180, accounting for 22.96% of the total number of quantum papers in the
world. This paper explores a novel metric model from the perspective of collaboration
academic position in co-authored papers to better understand China’s scientific
research strength in quantum technology.
Research strength analysis refers to measuring, comparing, and analyzing the
research status of different scientific research bodies (such as countries, institutions,
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Yuqi Wang et al.
Research Paper
Journal of Data and
Information Science
A Novel Metric for Assessing National Strength in Scientific Research: Understanding China’s
Research Output in Quantum Technology through Collaboration
http://www.jdis.org
https://www.degruyter.com/view/j/jdis
researchers, et al.) in various research fields (Ma et al., 2018). Bibliometrics is
commonly recognized as an efficient approach for measuring, comparing, and
assessing the performance/strength of scientists, institutions, and countries (Díaz-
Faes et al., 2015; Haeffner-Cavaillon & Graillot-Gak, 2009; Harnad, 2008; Inglesi-
Lotz & Pouris, 2011; Jia et al., 2014). The number of papers and citations are most
commonly used as the indicators (Liu & Mei, 2015; Mokhnacheva & Kharybina,
2011; Morris et al., 2003; Shibata et al., 2008; Small et al., 2014; Small & Upham,
2009). However, assessing scientific strength should be more constructive under
the background of seeking self-reliance and self-strengthening. Hence, the paper
provides a novel model synthesizing the national scientific self-reliance and the
national academic contribution.
The measure of scientific self-reliance and allocation of academic contribution is
essential for national research strength to assess in this paper, and there are many
ways to measure these two indicators. In this paper, scientific self-reliance refers
to the rate of independent publications and the degree of research autonomy in
collaboration based on the international collaboration patterns (Edler, 2010;
González-Alcaide et al., 2017; Kato & Ando, 2017; Zheng et al., 2014; Zou &
Laubichler, 2017). The previous studies on international collaboration are measured
mainly through various indicators, such as the number, share, and intensity from
different perspectives (Chen et al., 2019). However, previous studies only took into
account the number of papers published by the country as corresponding or first
author in international collaboration (Cho et al., 2010; Egghe, 1991), when they
calculated the dominance degree of a country, resulting in ignoring the dominance
of the country in other collaboration positions. Thus, in this paper, we propose five
collaboration dominance patterns based on the different academic positions of
countries to measure the degree of national scientific self-reliance in research
collaboration. Allocation of academic contribution is also essential for national
scientific research strength to assess, and it is one of the factors we consider in
building the metric model. Various methods have been proposed for calculating
academic contributions. The earliest method was the First Author Counting proposed
by Cole & Cole (1974), which only considered the contribution of the first author
and ignored the contribution of other authors. Lindsey (1980) used the Normal
Counting method, which allocated the same contribution weight to each author,
resulting in magnifying the secondary authors’ contributions and is unfair to the
primary authors. Besides, there are methods based on the order of authorship,
mainly including Fractional Counting (Charles & Oppenheim, 1998), Proportional
Counting (Abbas, 2010, 2011; Van Hooydonk, 1997), Geometric Counting (Egghe
et al., 2000), Harmonic Counting (Hagen, 2010; Hodge et al., 1981), Combined
Credit Allocation (Liu & Fang, 2012a, 2012b), Correct Credit Distribution (Lukovits
Journal of Data and Information Science Vol. 7 No. 4, 2022
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et al., 1995), and Network-based Allocation (Kim & Diesner, 2014). This method
is a significant improvement over the Normal Counting (Lindsey, 1980), taking into
account the effect of the number of authors and the rank of the byline on the size
of the contribution. It is worth noting that the Network-based Allocation can reorder
co-author sequences. If several corresponding authors are in a co-author sequence,
then the related authors can be reordered based on the magnitude of their contributions
before the contribution assignment. Based on the advantages of the Network-based
Allocation, we calculate the national academic contribution based on the author’s
signature position and the contribution transfer principle in designing the national
research strength metric model.
Considering the above model indicators, we explore a metric model for national
scientific research strength evaluation through cooperation on research papers.
The model mainly includes two indicators, national scientific self-reliance (SR)
and national academic contribution (CT), to reflect “self-reliance” and “self-
strengthening”, respectively. The measure of these two indicators takes into account
the author’s signature position and the citation frequency of the paper. The metric
model is applied in evaluating China’s quantum research strength.
The rest of the paper is organized as follows. In Section 2, the data collection and
methods used in this paper are described. In Section 3, we present the specific
experimental process and detailed results. Finally, we conclude the paper in Section 4.
2 Methodology and Data
2.1 National strength in scientific research
From the perspective of scientific research output, national strength in scientific
research for a country could be regarded as the country’s scientific contribution to
the world. Considering the contribution difference made by co-authors from different
countries at the paper level, this metric model sets two indicators to access the
national strength in scientific research for country i (SSi): a. the national contribution
to academic impact (CTi), b. the national scientific self-reliance for a country (SRi).
The metric model of national strength in scientific research is designed as follows:
SSi = CTi * SRi (1)
Where SSi is the scientific research strength index of country i, CTi is the academic
contribution of country i, SRi is the national scientific self-reliance index of country i.
2.2 National contribution to academic impact
The contribution distribution of each author in multi-author papers is complicated,
and there is no unified method for it. However, only considering the contribution
5
Yuqi Wang et al.
Research Paper
Journal of Data and
Information Science
A Novel Metric for Assessing National Strength in Scientific Research: Understanding China’s
Research Output in Quantum Technology through Collaboration
http://www.jdis.org
https://www.degruyter.com/view/j/jdis
of the first author, corresponding author, or the average distribution is unfair. Since
the author with the higher signature position in a paper makes more academic
contributions (the corresponding author is placed in the first place in the calculation
process). The author contribution transfer factor “d” is designed, which can be used
to determine the academic contribution transferred by the author with the lower
signature position to the author with the higher signature position in a paper. When
calculating the author’s academic contribution to the paper, the academic contribution
of the paper is evenly distributed to each collaborator, and then the author with the
lower signature position forwards part of his academic contribution to the author
with the higher signature position in turn. The size of the academic contribution
transferred is determined by the author’s contribution transfer factor “d”. Additionally,
the cited frequency is used for measuring the academic contribution of a paper
with multi-authors. The measure of the country’s academic contribution (CT) is
as follows:
1
1
**
−
∈=
⎡⎤
⎛⎞
=+ −
⎢⎥
⎜⎟
⎝⎠
−
⎣⎦
∑∑
ab
i
Mm
i
mm n
VV
CT d
MM Mn (2)
Where V is the cited frequency of the paper (V ≥ 1). M is the number of authors of
the paper. m is the order of authorship (1 ≤ m ≤ M), mi is a set of the order of
authorship belonging to country i. d is the author contribution transfer factor
(d = 0.5). a is the contribution benefit coefficient (a = 1), b is the contribution loss
coefficient (b = 1). It should be noted that if the author is in the first position (the
first author or the corresponding author), there will be no contribution loss for the
author, then b = 0. If the author is in the last position, there will be no contribution
gain for the author, then a = 0.
2.3 National scientific self-reliance
The national scientific self-reliance (SR) for a country shows the autonomy
intensity in research, which can be reflected by the complete independence in the
paper produced by a country and the national autonomy in the multi-countries paper.
Based on this principle, this paper designs the national scientific self-reliance index
(SR) to more comprehensively consider the scientific research dominant degree of
a country in a certain field.
*1*
→
∈
⎛⎞
⎛⎞
=+−
⎜⎟
⎜⎟
⎝⎠
⎝⎠
∑
i
t
tt
ij
ii
i i j indep
tt t
j Corp
ii i
N
NN
SR Autonomy Autonomy
SN S (3)
where t
i
Nis the total number of cooperative papers produced by country i with other
countries at time t,t
i
Sis the total number of papers produced by country i at time t.
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Corpi is the set of cooperating countries for country i.t
ij
Nis the number of cooperative
papers of countries i and j at time t.
For the national scientific self-reliance shown by the country’s independent
publications, this paper calculates the proportion of independent papers published
by country i to all papers published by country i in this field. As shown on the right
side of the plus sign in equation 3, where 1
⎛⎞
−
⎜⎟
⎝⎠
t
i
t
i
N
S is the proportion of independently
published papers in the country i, Autonomyindep is the research autonomy index
demonstrated by the independent publication of country i, and its value is 1.
For the national scientific self-reliance shown by the country collaborated with
other countries, we first calculate the proportion of the multi-countries papers
published by country i to all papers published by country i, and then calculate the
sum of scientific research autonomy between the country i and all its collaborated
countries, which are referred as “j” in equation 3, and finally multiply the two values.
As shown on the left side of the plus sign in equation 3, where
t
i
t
i
N
S
is the proportion
of multi-countries papers published by country i, Autonomyi→j is the research
autonomy index of country i in research collaboration between countries i and j.
*→
∈
⎛⎞
⎜⎟
⎝⎠
∑
i
t
ij
ij
t
j Corp i
NAutonomy
N is the sum of the scientific research autonomy of country
i to each country j in cooperation.
The autonomy we consider here is based on collaboration between two countries.
For example, to the cooperative countries, country i and country j, the national
autonomy of country i (Autonomyi→j) is calculated by subtracting the dominant
degree of country j()
→
t
ji
Dominant from the dominant degree of country i
()
→
t
ij
Dominant . The calculation method is as follows:
Autonomy →→→
=−
tt
ij ij ji
Dominant Dominant (4)
Where the research autonomy index (Autonomyi→j) takes values in the range (-1,1),
if Autonomyi→j ≤ 0, then country i has no research autonomy with country j. if
Autonomyi→j > 0, country i exists research autonomy with country j. The closer the
value of the research autonomy index is to 1, the stronger the research autonomy
of country i in research collaboration.
In previous studies, when calculating the dominant degree of country i over
country j, the number of papers in which country i was the corresponding or first
author during the collaboration was counted (Cho et al., 2010; Egghe, 1991). Here,
the concept of cooperative position is introduced to assess the national dominant
degree of a country. Firstly, all the participant countries are divided into three types
7
Yuqi Wang et al.
Research Paper
Journal of Data and
Information Science
A Novel Metric for Assessing National Strength in Scientific Research: Understanding China’s
Research Output in Quantum Technology through Collaboration
http://www.jdis.org
https://www.degruyter.com/view/j/jdis
according to the signature position. (1) The dominant country plays a leading role
in a paper and is decided by the corresponding author and the first author. Generally,
the corresponding author is the leader of the research project and responsible for
the design, organization, and planning, and the first author is the main writer of the
paper. They are both the dominator of the paper. (2) The largest contribution country
is decided by the national contribution to academic impact (CTi) based on the
principle of contribution transfer. Although the corresponding author and the first
author dominate a paper, other collaborators’ contributions should be accounted.
(3) The subordinate country is the cooperative country which is neither dominant
nor the largest contributor (Wang, 2014). Secondly, any two cooperative countries,
such as country i and country j could be located in the different positions in
Table 1, and to country i, it exists five collaboration dominance patterns (Strongly
dominant, Substrongly dominant, Dominant, Subweakly dominant, Weakly
dominant), five different weights are assigned respectively to calculate the dominant
degree of country i to country j )( →
t
ij
Dominant . The sum of the five weights wk is
1, and their values are equidistantly decreasing in order, that is, 5/15, 4/15, 3/15,
2/15, 1/15 respectively.
5
1
→
=
→=∑ij
t
kk
k
t
ij t
ij
NW
Dominant N (5)
Where →ij
t
k
Nis the number of cooperative papers of country i and country j at time
t in collaboration pattern k with the weight (wk). t
ij
Nis the total number of collaborative
papers of country i and country j at time t. The greater →
t
ij
Dominant indicates, the
stronger the leading role played by country i to country j at time t.
Table 1. Five dominance patterns of Dominanti→j.
Collaboration patterns Dominant country Largest contributing country Subordinate country Weight
Strongly dominant i i j 5/15
Substrongly dominant ij 4/15
Dominant ij3/15
Subweakly dominant ij2/15
Weakly dominant i j1/15
2.4 Data Source
The data used for this method was collected from the Web of Science (WoS)
database. We utilize the following search strategy (Zhang et al., 2018) for quantum
technology papers which is based on the website of qurope.eu (BINOSI &
CALARCO, 2017): TS=((“Quantum” and ((“information”) OR (“eraser”) OR
(“Quantum Classical Transition”) OR (“coherence”) OR (“entanglement”)
OR (“measurement”) OR (“network”) OR (“storage”) OR (“memory”) OR
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(“communication”) OR (“fingerprint”) OR (“processor”) OR (“Cavity QED”) OR
(“clock synchronization”) OR (“image”) OR (“sensor”) OR (“magnetometry”))) OR
((quantum NEAR/5 comput*) OR (quantum NEAR/15 algorithm*) OR (quantum
NEAR/10 simulat*) OR (quantum NEAR/10 error*) OR (“quantum circuit”
OR “Quantum cellular automata” OR “Quantum Turing machine” OR “quantum
register”) OR (quantum NEAR/10 communication*) OR (quantum NEAR/15
protocol*) OR (quantum NEAR/15 cryptograph*) OR (“quantum key”))).
We retrieved and downloaded paper data (Article and Review) from 1990 to 2021
in the WoS database for the bibliometric analysis (as of July 2021). Then We
performed data cleaning, including removing duplicates and data with missing C1
fields. Finally, we collected a total of 175,002 publication records published by 147
countries. Each record has 30 meta-data fields: authors, title, affiliation, abstract,
keywords, publication source, and reference list. All data processing, calculation,
and exploration were conducted via python scripts.
3 Results
3.1 China’s position in the global collaboration network in quantum
technology
The United States (US) and China are the top two countries based on the number
of papers published in quantum technology, followed by Germany and England.
There are 147 countries that publish 175,002 quantum technology papers, and
75.69% of the total papers are posted by the top 10 countries with the highest
publications (see Table 2(a)). There are 40,180 papers are from China, accounting
for 22.96% of 175,002 papers, and 24.57% of them are published by multi-countries.
The international collaboration rate is the lowest compared to the top 10 highly
productive countries in quantum technology research, and the majority (10.58%)
collaborated with the US (see Table 2(b)). Compared with European countries,
especially Germany, England, and France, Asian countries, such as China, India,
and Japan, are more independent with lower collaboration rates (in this case,
24.57%, 30.82%, and 39.85%, respectively).
The development stage of quantum technology is manifested in the logistic
growth curve by fitting the accumulation of literature. There is a goodness of fit
with R2 = 0.919, and the model can effectively predict the development stage of
quantum technology research (see Fig. 1). At present, the exponential growth period
has just ended, and the number of papers will still increase. What’s more, the model
also presents the degree of quantum technology maturity and its corresponding
time, that is, 0.1 (2003), 0.5 (2018), 0.9 (2034), and 0.99 (2049). China’s paper
amount surpassed the US’s in 2013 and surpassed Europe’s in 2020. China has been
9
Yuqi Wang et al.
Research Paper
Journal of Data and
Information Science
A Novel Metric for Assessing National Strength in Scientific Research: Understanding China’s
Research Output in Quantum Technology through Collaboration
http://www.jdis.org
https://www.degruyter.com/view/j/jdis
a big nation with the most significant number of papers and shows a continued
growth trend in quantum technology research.
Figure 1. The growth trend of papers of quantum technology by China, USA, and Europe.
Note: The dotted line without dots is the predicted value in the cumulative growth curve.
Cooperation in scientific research is essential for a country to participate in global
development. A country’s position in the global cooperation network can reflect
its own scientific and technological strength, and reflect its dominant power in
future scientific and technological development. In this study, we construct a
network of national scientific collaboration in the field of quantum technology (see
→ ⎡⎢
⎢
⎢
⎢
⎢
⎣
Table 2. Top 10 countries with the highest number of papers in quantum technology (a) and China’s research
collaboration layout (b).
(a) (b)
No. Country Number of
Papers
Collaboration
Papers
Collaboration
Proportion
Collaboration
countries
Collaboration
strengtha
Collaboration
Papers
1 USA 40,906 18,665 45.63% USA 0.11 5,318
2 China 40,180 9,871 24.57% Singapore 0.08 977
3 Germany 18,633 11,937 64.06% Australia 0.06 1,040
4 England 11,904 7,816 65.66% Germany 0.05 1,714
5 Japan 11,726 4,673 39.85% Japan 0.05 1,215
6 France 9,002 6,000 66.65% Canada 0.04 952
7 Italy 8,937 5,271 58.98% England 0.04 1,087
8 Canada 7,409 4,812 64.95% Pakistan 0.04 259
9 India 7,394 2,279 30.82% South Korea 0.04 604
10 Russia 6,252 3,241 51.84% Saudi Arabia 0.03 1,040
Note: aCollaboration strength is calculated with Salton formula (Salton, 1983)
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Fig. 2). The strength of collaboration between countries along the Belt and Road,
such as Sri Lanka, Cyprus, Georgia, Estonia, and Egypt, is the highest in the
international research collaboration network. Although the number of collaborations
among these countries is minimal, the strength of collaboration is among the top
globally (see Table 3). The US and European countries emphasize international
collaboration, but most are European countries. China is more independent in
quantum research, with a large proportion of papers on its own. There are only 9,817
multi-nations papers collaborated with 99 countries in China’s 40,180 quantum
research papers. Most cooperation partners come from developed countries, such as
the US, Singapore, Germany, England, et al. (see Table 2(b)).
Figure 2. Research collaboration strength network in the fi eld of quantum technology.
Note: The nodes represent countries that have published papers in quantum technology. The edges represent the
scientifi c collaboration between countries. The weights of the edges represent the strength of collaboration
between countries calculated by the Salton formula (Salton, 1983). The node size represents the size of
the betweenness centrality of a country, and the larger the node, the more collaboration resources the country
controls. The thickness of the lines represents the collaboration strength, and the thicker the lines, the stronger
the collaboration strength between the two countries. We selected 53 countries based on their collaboration
strength (> 0.06).
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A Novel Metric for Assessing National Strength in Scientific Research: Understanding China’s
Research Output in Quantum Technology through Collaboration
http://www.jdis.org
https://www.degruyter.com/view/j/jdis
Table 3. Top 5 collaboration countries with the highest collaboration strength in quantum technology.
No. Collaboration country (Number of papers) Collaboration strengthaCollaboration papers
1 Sri Lanka (64); Cyprus (109) 0.51 43
2 Sri Lanka (64); Georgia (139) 0.46 43
3 Estonia (189); Sri Lanka (64) 0.39 43
4 Cyprus (109); Georgia (139) 0.38 47
5 Egypt (1,386); Saudi Arabia (1,567) 0.36 528
Note: aCollaboration strength is calculated with Salton formula (Salton, 1983)
Table 4. Statistics of the network centrality for the top 10 countries with the highest betweenness centrality
in quantum technology.
No. Country Betweenness Centrality Degree Centrality Closeness Centrality
1 France 0.0700 106 0.7650
2 South Africa 0.0607 90 0.7083
3 USA 0.0594 111 0.7846
4 Germany 0.0518 106 0.7650
5 Spain 0.0516 94 0.7183
6 China 0.0427 99 0.7391
7 England 0.0421 105 0.7612
8 India 0.0384 94 0.7217
9 Canada 0.0367 92 0.7116
10 Sweden 0.0335 89 0.7018
Global quantum research is dominated by the US and Europe (i.e. England,
France, Germany) with high betweenness centrality, which refers to the ability to
control information resources in a network (Brandes, 2001). By contrast, China’s
network centrality indexes are lower, betweenness ranked 6th, degree ranked 5th, and
Closeness ranked 5th, well below the 2nd ranking by papers amount (see Table 4).
3.2 China’s academic contribution in quantum technology
Based on the proposed indicator CTi (see Equation 2), China is the second-largest
contributor to quantum technology, accounting for 12.6% of the whole world’s
contribution, and is the unique developing country ranked in the top 10 countries
(see Table 5). Besides, although the US’s total contribution proportion (i.e. 30.57%,
see Table 6) is much higher than China’s, it presents a decreasing trend year by year
(see Fig. 3 left), from 38.08% in 2001 to 17.82% in 2020. By contrast, China’s
contribution proportion significantly increased from 3.25% in 2001 to 27.81% in
2020 (see Fig. 3 right), much higher than that of the US in 2020. The same trend
is also observed in the total contribution proportion of developed countries vs.
developing countries. It is worth noting that the proportion of papers with zero
citation in developing countries is much higher than that in developed countries, for
example, 5.44% in USA, 4.01% in Germany and 3.70% in England, by contrast,
12.14% in China, 12.25% in India and 11.53% in Russia. (cf., Appendix 1)
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Table 5. Ranking of academic contribution (CT) in global quantum technology.
No. Country CT Contribution
proportion No. Country CT Contribution
proportion
1 USA 1,593,667.96 30.57% 75 Cameroon 364.35 0.007%
2 China 639,792.41 12.28% 76 Iceland 358.65 0.007%
3 Germany 471,644.89 9.05% 77 Moldova 332.54 0.006%
4 England 317,155.23 6.08% 78 Indonesia 326.91 0.006%
5 Japan 230,317.08 4.42% 79 Ethiopia 294.08 0.006%
6 Italy 199,203.76 3.82% 80 Philippines 291.82 0.006%
7 France 198,179.40 3.80% 81 Czechoslovakia 281.92 0.005%
8 Canada 163,038.66 3.13% 82 Kazakhstan 238.84 0.005%
9 Austria 154,559.69 2.96% 83 Jordan 213.80 0.004%
10 Switzerland 135,561.92 2.60% 84 Kuwait 206.25 0.004%
11 Spain 113,040.28 2.17% 85 Sri Lanka 200.63 0.004%
12 Australia 111,733.35 2.14% 86 Oman 196.78 0.004%
13 India 91,204.80 1.75% 87 Lebanon 162.98 0.003%
14 Netherlands 80,271.91 1.54% 88 Malta 155.93 0.003%
15 South Korea 62,339.05 1.20% 89 Brunei 98.70 0.002%
16 Russia 61,630.01 1.18% 90 Azerbaijan 92.67 0.002%
17 Israel 60,244.46 1.16% 91 Palestine 83.25 0.002%
18 Poland 51,529.10 0.99% 92 Macedonia 81.75 0.002%
19 Sweden 46,708.93 0.90% 93 Vatican 74.46 0.001%
20 Brazil 41,762.49 0.80% 94 Bosnia & Herceg 72.07 0.001%
... ... ... ... ... ... ... ...
74 Bahrain 368.82 0.007% 147 Eritrea 0.23 0.000004%
Note: Developing countries in gray background. The basis for the division between developed and developing
countries is the Word Economic Outlook(International Monetary Fund, 2018), in which International Monetary
Fund (IMF) divides 193 countries into two categories: 39 developed countries and 154 developing countries.
CT see Equation 2 in Section 2.
Contribution Proportion =i
i
CT
Total CT
3.3 China’s research autonomy in quantum scientific collaboration
In this section, we try to understand China’s research autonomy in quantum
scientific collaboration through the research autonomy index (Autonomyi→j) (see
Equation 4) (see Table 6).
As shown in Table 6, China’s dominance over the US is 20.02%, while the US’s
dominance over China is 10.36%. Thus the research autonomy index for China over
the US (AutonomyChina→US) is 9.66%, indicating that China has research autonomy
in Sino-US research collaboration. Overall, among the 31 developed countries
cooperating with China, 28 countries have lower dominance than China, only two
countries (i.e. Iceland and New Zealand) have higher dominance, and one country
(Malta) has the same dominance as China (see Table 7). Among 68 developing
countries cooperating with China, the corresponding number of countries is 42, 11,
and 15 respectively. The results show that China plays a leading role in international
13
Yuqi Wang et al.
Research Paper
Journal of Data and
Information Science
A Novel Metric for Assessing National Strength in Scientific Research: Understanding China’s
Research Output in Quantum Technology through Collaboration
http://www.jdis.org
https://www.degruyter.com/view/j/jdis
Figure 3. Changes in the contribution of China and the US in developed and developing countries.
Note: The fi rst column on the left represents the developed countries’ contribution proportion from 2001 to
2020. The second column on the left represents the USA’s contribution proportion from 2001 to 2020. The fi rst
column on the right represents the developing countries’ contribution proportion from 2001 to 2020. The
second column on the right represents China’s contribution proportion from 2001 to 2020.
Table 6. Partial results of the research autonomy in national research collaboration (ranking by China’s
collaboration strength)
China USA Singapore Japan Australia ... Algeria
China ↙10.36%
↑-9.66%
↙10.66%
↑-9.05%
↙11.76%
↑-5.10%
↙9.53%
↑-10.84%
↙6.67%
↑0
USA ↙20.02%
↑9.66%
↙12.97%
↑0.09%
↙12.92%
↑-1.58%
↙14.18%
↑0.91%
↙12.38%
↑1.90%
Singapore ↙19.71%
↑9.05%
↙12.88%
↑-0.09%
↙15.87%
↑5.333%
↙15.22%
↑4.03%
↙0.00%
↑0
Japan ↙16.86%
↑5.10%
↙14.51%
↑1.58%
↙10.54%
↑-5.33%
↙15.79%
↑5.53%
↙33.33%
↑33.33%
Australia ↙20.37%
↑10.84%
↙13.28%
↑-0.91%
↙11.19%
↑-4.03%
↙10.26%
↑-5.53%
↙0.00%
↑-33.33%
... ... ...
Algeria ↙6.67%
↑0
↙10.48%
↑-1.90%
↙0.00%
↑0
↙0.00%
↑-33.33%
↙33.33%
↑33.33%
...
Notes:
↙represents the →
t
ij
Dominant (see Equation 5) for the dominance of country i (column label) over the country
j (row label);
↑represents the Autonomyi→j (see Equation 4) for measuring the dominance difference between country i
(column label) and country j (row label), the positive value represents the dominance of country i is higher than
country j, and the negative value represents the opposite results.
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collaboration in quantum technology, whether the collaboration countries are
developed or developing countries.
The distribution of the proportion of papers in five dominance patterns for China-
leading research collaboration in quantum technology is listed in Table 8. We found
that China often plays a role as the dominant country (the first row in Table 8), and
the largest contribution country when collaborating with the developed countries.
In particular, China mainly cooperates as the strongly dominant type with the US,
Germany, England, and Japan. By contrast, as the weak dominant type with the
developing countries (the 9th row in Table 8). We explain the results as, developed
countries have strong research strength in quantum technology, and China is more
active in the cooperation with developed countries. Therefore, China often prefers
to lead the cooperation with developed countries. However, the weak research
strength of developing countries, China’s cooperation attitude with developing
countries in this field is relatively negative and China often participates together
with the developing country as the subordinate country in the collaboration
dominated by other countries.
Table 8. Distribution of the proportion of papers in the five dominance patterns of DominantChina→countries.
China Strongly
dominant
Substrongly
dominant Dominant Subweakly
dominant
Weakly
dominant
Developed Countries 64.13% 1.64% 1.01% 1.26% 31.96%
USA 79.99% 2.39% 0.65% 1.30% 15.66%
Germany 66.77% 0.81% 1.21% 0.70% 30.51%
England 63.17% 1.02% 1.89% 0.87% 33.04%
Japan 67.23% 1.38% 0.61% 2.60% 28.18%
France 41.99% 1.10% 1.38% 1.10% 54.42%
Italy 49.40% 5.22% 0.80% 2.01% 42.57%
Canada 69.73% 1.44% 1.26% 1.08% 26.49%
Developing Countries 29.75% 0.51% 1.06% 1.24% 67.44%
India 42.52% 2.80% 1.40% 2.34% 50.93%
Russia 31.58% 0.38% 1.88% 0.75% 65.41%
Note: The five dominance patterns are classified based on Table 1.
DominantChina→countries represents China’s dominance in scientific research cooperation with developed/
developing countries.
The countries are selected based on the number of their papers published in quantum technology (see
Table 2(a)).
Table 7. Distribution of the number of countries with AutonomyChina→countries.
AutonomyChina→countries > 0 AutonomyChina→countries < 0 AutonomyChina→countries = 0
Developed countries (31) 28 2 1
Developing countries (68) 42 11 15
Note: In the row label, (31) and (68), represents the number of developed and developing countries in our
datasets respectively. AutonomyChina→countries represents the dominance difference between China and developed/
developing countries.
15
Yuqi Wang et al.
Research Paper
Journal of Data and
Information Science
A Novel Metric for Assessing National Strength in Scientific Research: Understanding China’s
Research Output in Quantum Technology through Collaboration
http://www.jdis.org
https://www.degruyter.com/view/j/jdis
3.4 China’s national strength in quantum scientific research
China’s SS value is second only to the United States according to eq uation 1 (see
Table 9), indicating that the US and China have become the most prominent countries
in quantum technology. There are 12 developed countries vs. 3 developing countries
(China, India, and Russia) ranked among the top 10% with highly SS. With the
exception of China, India, and Russia, most developing countries are weaker in
scientific research strength. The national scientific self-reliance (SR) for a country
shows the autonomy intensity in research, which can be reflected by the complete
independence in the paper produced by a country and the national autonomy in the
multi-countries paper. Therefore, China’s high SR is caused by the high proportion
of independent publications and high autonomy in research cooperation. And the
similar result is also observed in India’s SR, as seen in Table 1, where the proportion
of research collaboration is only 30.82%. However, high SR does not indicate high
SS, for example, India has high SR but low SS and the US has low SR but high SS,
the same can be applied to Germany and the UK. While China is special with both
high SR and SS.
Table 9. Ranking of scientific research strength index (SS) in global quantum technology.
No. Country SR SS No. Country SR SS
1 USA 0.54 853,088.21 75 Philippines 0.22 63.31
2 China 0.77 493,650.57 76 Moldova 0.19 61.86
3 Germany 0.36 170,519.88 77 Indonesia 0.16 51.88
4 Japan 0.59 136,364.59 78 Macedonia 0.62 50.78
5 England 0.33 105,841.36 79 Kazakhstan 0.21 49.26
6 Italy 0.42 84,291.22 80 Jordan 0.21 45.08
7 India 0.70 63,615.28 81 Cuba 0.07 41.72
8 France 0.32 63,100.22 82 Qatar 0.03 35.43
9 Canada 0.34 54,791.26 83 Jamaica 0.61 34.89
10 Austria 0.28 43,443.24 84 Serbia Monteneg 0.53 30.53
11 Switzerland 0.28 37,720.08 85 Bahrain 0.08 29.09
12 Australia 0.33 36,955.01 86 Oman 0.14 27.10
13 Spain 0.31 34,742.01 87 Sri Lanka 0.12 24.12
14 South Korea 0.55 34,124.41 88 Brunei 0.24 23.50
15 Russia 0.46 28,491.90 89 North Korea 0.33 23.45
16 Iran 0.77 23,826.65 90 Malta 0.14 21.40
17 Israel 0.37 22,480.51 91 North Macedonia 0.29 19.60
18 Netherlands 0.27 21,887.75 92 Lebanon 0.10 15.97
19 Brazil 0.52 21,704.77 93 Bosnia & Herceg 0.15 11.01
20 Poland 0.41 20,901.86 94 Azerbaijan 0.10 9.32
…… … …… … ……
74 Cyprus 0.08 29.09 147 Panama -0.08 -5.01
Note: Developing countries in gray background
SR see Equation 3 in Section 2
SS see Equation 1 in Section 2
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The national scientific self-reliance index (SRi) trends for the top five developed
countries and the top five developing countries with highly SS are shown in Fig. 4.
Overall, the values of SR of the five developed countries (i.e. USA, Germany,
Japan, England, Italy) all show declining trends, but their relative positions remain
unchanged (Fig. 4 left). The values of SR of the US and Japan are higher than the
other three European countries, Germany, England, and Italy. The developing
countries, except Brazil, all show a slowly increasing or steady trend (Fig. 4 right).
In particular, China kept the highest value of SR over time, and Iran’s SR increased
significantly and caught up with China in 2006. Brazil’s SR began to decline
significantly after 2011, and then it remained flat with Russia. It shows that the
proportion of developed countries published independently in quantum technology
and the research autonomy in scientific collaboration is constantly decreasing. The
proportion of developing countries, especially Iran, independently published papers
in quantum technology, and their research autonomy in scientific collaboration has
been dramatically improved. Although China’s scientific self-reliance index in
quantum technology has risen slightly, it is relatively stable. China has always
maintained high independence in the development process of quantum technology.
Figure 4. The time trend of national scientifi c self-reliance index (SR).
Fig. 5 shows that the US’s SS ranked first between 2001 and 2011, but China
overpassed the US and became the top one based on SS. The SS rankings of Japan,
Germany, Italy, and England have fallen in the past 10 years but are still among the
top 10 SS rankings in the world. China is the unique developing country in the top
5 SS rankings and has been ranked 1st since 2012, surpassing the US to become the
global leader in the quantum technology area.
17
Yuqi Wang et al.
Research Paper
Journal of Data and
Information Science
A Novel Metric for Assessing National Strength in Scientific Research: Understanding China’s
Research Output in Quantum Technology through Collaboration
http://www.jdis.org
https://www.degruyter.com/view/j/jdis
Figure 5. The time trend of national rankings based on scientifi c research strength index (SS).
Besides, the position of the other three developing countries, India, Russia, and
Iran, in global quantum technology is also continuously rising and has been in the
top 10 SS rankings in 2020. Especially Iran, which has risen from 61st in 2001 to
4th in 2020, having taken a significant position in driving quantum technology
development. The results indicate that while developed countries have strong
scientific research strength in the quantum field, some developing countries have
shown increasing contribution to this area, and scientific autonomy, as well as
scientific strength.
4 Conclusions
This paper explores a metric model for assessing national strength in scientific
research to understand China’s research output in quantum technology through
collaboration. To this end, we propose two indicators from two perspectives: the
national contribution to academic impact and the scientific self-reliance, to measure
and assess China’s scientific research strength and make a comparison with the US
and other outstanding countries in global quantum technology, such as Germany,
England, Japan, and Italy in developed countries and Russia, India, Iran, and Brazil
in developing countries.
Our results lend support to China’s prominent position in quantum technology
currently (Smith-Goodson, 2019) measured by the metric model of national strength
in scientific research. The proportion of international collaboration papers of China
is lower and the research on quantum technology in China locates in a more marginal
position in global cooperation networks. However, China’s total contribution to
quantum technology is ranked the world 2nd, and its annual contribution has surpassed
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the US since 2015. The gradually increasing advantage for China vs. USA is also
witnessed in Fig. 3, measured by the indicator national academic contribution (CT).
What’s more, China shows a higher scientific autonomy in international collaboration
measured by the research autonomy indicator (Autonomyi→j) and exhibits different
dominant patterns: Strongly dominant type is found when China dominates the
research collaboration with developed countries, especially with the US, Germany,
England, Japan, and Canada; While weakly dominant type is found when China
dominates the research collaboration with developing countries. It’s an interesting
result and more data are needed to explore the reason behind it in further research,
for instance, the relationship between the results and Journal Impact Factor or
citations.
China’s scientific self-reliance is gradually increasing (see Fig. 4 right) and its
scientific strength in quantum technology has surpassed the US, and taken a world
prominent position (see Fig. 5). Some other developing countries, such as India,
Russia, and Iran, which have also recognized the strategic importance of quantum
technology and continue making more efforts in this area (Fedorov et al., 2019;
Padma, 2020; Salehi, 2021), have shown increasing participation in quantum
research, significantly eroding the developed countries’ lead (i.e. Germany, Japan,
England, Italy) in the global quantum technology race.
Funding information
This work is supported by National Key R&D Program of China (Grant No.
2019YFA0707201), and the open fund of ISTIC-Springer Nature Joint Lab for Open
Science (Grant No. HX20211292).
Author contributions
Yuqi Wang (wangyuqi2019@126.com): Conceptualization (Equal), Data curation (Equal),
Methodology (Equal); Yue Chen (chenyuedlut@163.com): Conceptualization (Equal),
Methodology (Equal); Zhiqi Wang (zhiqi_wang@dlut.edu.cn): Formal analysis (Supporting);
Kang Wang (wangkangdult@163.com): Data curation (Equal); Kai Song (Songkai1105@mail.
dlut.edu.cn): Formal analysis (Supporting).
References
Abbas, A.M. (2010). Generalized Linear Weights for Sharing Credits Among Multiple Authors.
arXiv:1012.5477 [cs]. http://arxiv.org/abs/1012.5477
Abbas, A.M. (2011). Weighted indices for evaluating the quality of research with multiple
authorship. Scientometrics, 88(1), 107–131. https://doi.org/10.1007/s11192-011-0389-7
BINOSI, D., & CALARCO, T. (2017). Quantum Information Classification Scheme-QICS. http://
qurope.eu/content/qics-book
19
Yuqi Wang et al.
Research Paper
Journal of Data and
Information Science
A Novel Metric for Assessing National Strength in Scientific Research: Understanding China’s
Research Output in Quantum Technology through Collaboration
http://www.jdis.org
https://www.degruyter.com/view/j/jdis
Bornmann, Lutz, Leydesdorff, Loet, Wagner, Caroline, & S. (2015). Recent Developments in
China-US Cooperation in Science. Minerva: A Review of Science, Learning and Policy, 53(3),
199–214.
Brandes, U. (2001). A faster algorithm for betweenness centrality. The Journal of Mathematical
Sociology, 25(2), 163–177. https://doi.org/10.1080/0022250X.2001.9990249
Charles & Oppenheim. (1998). Fractional counting of multiauthored publications. Journal of the
American Society for Information Science, 49(5), 482–482. https://doi.org/10.1002/(sici)1097-
4571(19980415)49:5<482::aid-asi11>3.3.co;2-8
Chen, K.H., Zhang, Y., & Fu, X.L. (2019). International research collaboration: An emerging
domain of innovation studies? Research Policy, 48(1), 149–168. https://doi.org/10.1016/
j.respol.2018.08.005
Cho, C.-C., Hu, M.-W., & Liu, M.-C. (2010). Improvements in productivity based on co-authorship:
A case study of published articles in China. Scientometrics, 85(2), 463–470. https://doi.
org/10.1007/s11192-010-0263-z
Cole, J.R., & Cole, S. (1974). Social Stratification in Science. American Journal of Physics, 42(10),
923–924. https://doi.org/10.1119/1.1987897
Díaz-Faes, A.A., Costas, R., Galindo, M.P., & Bordons, M. (2015). Unravelling the performance
of individual scholars: Use of Canonical Biplot analysis to explore the performance of
scientists by academic rank and scientific field. Journal of Informetrics, 9(4), 722–733.
https://doi.org/10.1016/j.joi.2015.04.006
Edler, J. (2010). International Policy Coordination for Collaboration in S&T (SSRN Scholarly
Paper ID 1542583). Social Science Research Network. https://doi.org/10.2139/ssrn.1542583
Egghe, L. (1991). Theory of collaboration and collaborative measures. Information Processing &
Management, 27(2), 177–202. https://doi.org/10/b84gmq
Egghe, L., Rousseau, R., & Van Hooydonk, G. (2000). Methods for accrediting publications to
authors or countries: Consequences for evaluation studies. Journal of the American Society
for Information Science, 51(2), 145–157. https://doi.org/10.1002/(SICI)1097-4571(2000)51:2
<145::AID-ASI6>3.0.CO;2-9
Fedorov, A.K., Akimov, A.V., Biamonte, J.D., Kavokin, A.V., Khalili, F.Y., Kiktenko, E.O.,
Kolachevsky, N.N., Kurochkin, Y.V., Lvovsky, A.I., Rubtsov, A.N., Shlyapnikov, G.V.,
Straupe, S.S., Ustinov, A.V., & Zheltikov, A.M. (2019). Quantum technologies in Russia.
Quantum Science and Technology, 4(4), 040501. https://doi.org/10.1088/2058-9565/ab4472
González-Alcaide, G., Park, J., Huamaní, C., & Ramos, J.M. (2017). Dominance and leadership in
research activities: Collaboration between countries of differing human development is
reflected through authorship order and designation as corresponding authors in scientific
publications. PLOS ONE, 12(8), e0182513. https://doi.org/10/gbqt6b
Haeffner-Cavaillon, N., & Graillot-Gak, C. (2009). The use of bibliometric indicators to help
peer-review assessment. Archivum Immunologiae et Therapiae Experimentalis, 57(1), 33.
https://doi.org/10.1007/s00005-009-0004-2
Hagen, N.T. (2010). Harmonic publication and citation counting: Sharing authorship credit
equitably—not equally, geometrically or arithmetically. Scientometrics, 84(3), 785–793.
https://doi.org/10.1007/s11192-009-0129-4
Harnad, S. (2008). Validating Research Performance Metrics Against Peer Rankings. Ethics in
Science & Environmental Politics, 8(1), 111–120. https://doi.org/10.3354/esep00088
Journal of Data and Information Science Vol. 7 No. 4, 2022
20
Research Paper
Journal of Data and
Information Science
He, T.W. (2009). International scientific collaboration of China with the G7 countries. Scientometrics,
80(3), 571–582. https://doi.org/10.1007/s11192-007-2043-y
Hodge, S.E., Greenberg, D.A., & Challice, C.E. (1981). Publication Credit. Science, 213(4511),
950–952.
Inglesi-Lotz, R., & Pouris, A. (2011). Scientometric impact assessment of a research policy
instrument: The case of rating researchers on scientific outputs in South Africa. Scientometrics,
88(3), 747. https://doi.org/10.1007/s11192-011-0440-8.
International Monetary Fund. (2018). World Economic Outlook, April 2018: Cyclical Upswing
Structural Change. IMF. https://www.imf.org/en/Publications/WEO/Issues/2018/03/20/
world-economic-outlook-april-2018
Jia, Z.J., Hong, B., Chen, D.M., Huang, Q.H., Yang, Z.G., Yin, C., Deng, X.Q., & Liu, J.M. (2014).
China’s Growing Contribution to Global Intracranial Aneurysm Research (1991–2012): A
Bibliometric Study. PLOS ONE, 9(3), e91594. https://doi.org/10.1371/journal.pone.0091594
Kato, M., & Ando, A. (2017). National ties of international scientific collaboration and researcher
mobility found in Nature and Science. Scientometrics, 110(2), 673–694. https://doi.org/10/
f9vc64
Kim, J., & Diesner, J. (2014). A network-based approach to coauthorship credit allocation.
Scientometrics, 101(1), 587–602. https://doi.org/10.1007/s11192-014-1253-3
Lindsey, D. (1980). Production and Citation Measures in the Sociology of Science: The Problem
of Multiple Authorship. Social Studies of Science, 10(2), 145–162. https://doi.org/10.1177/
030631278001000202
Liu, J., & Mei, Y.E. (2015). Research on the Subject Development Forecast Based on ESl and
lnCites—Taking China University of Geosciences as an Example. Sci-Tech Information
Development & Economy. http://en.cnki.com.cn/Article_en/CJFDTotal-KJQB201506056.htm
Liu, X.Z., & Fang, H. (2012a). Fairly sharing the credit of multi-authored papers and its application
in the modification of h-index and g-index. Scientometrics, 91(1), 37–49. https://doi.org/
10.1007/s11192-011-0571-y
Liu, X.Z., & Fang, H. (2012b). Modifying h-index by allocating credit of multi-authored papers
whose author names rank based on contribution. Journal of Informetrics, 6(4), 557–565.
https://doi.org/10.1016/j.joi.2012.05.002
Lukovits, I., & Vinkler, P. (1995). Correct credit distribution: A model for sharing credit... Social
Indicators Research. http://search.ebscohost.com/login.aspx?direct=true&db=aph&AN=960
1233217&site=ehost-live
Ma, T.C., Li, R.N., Ou, G.Y., & Yue, M.L. (2018). Topic based research competitiveness evaluation.
Scientometrics, 117(2), 789–803. https://doi.org/10.1007/s11192-018-2891-7
Mallapaty, S. (2021). China’s five-year plan focuses on scientific self-reliance. Nature, 591(7850),
353–354. https://doi.org/10.1038/d41586-021-00638-3
Mokhnacheva, Yu, V., & Kharybina, T.N. (2011). Research performance of RAS institutions and
Russian universities: A comparative bibliometric analysis. Herald of the Russian Academy of
Sciences, 81(6), 569–574. https://doi.org/10.1134/S1019331611060104
Morris, S.A., Yen, G., Wu, Z., & Asnake, B. (2003). Time line visualization of research fronts.
Journal of the American Society for Information Science and Technology, 54(5), 413–422.
Padma, T.V. (2020). India bets big on quantum technology [News]. Nature. https://www.nature.
com/articles/d41586-020-00288-x
21
Yuqi Wang et al.
Research Paper
Journal of Data and
Information Science
A Novel Metric for Assessing National Strength in Scientific Research: Understanding China’s
Research Output in Quantum Technology through Collaboration
http://www.jdis.org
https://www.degruyter.com/view/j/jdis
Salehi, A.A. (2021). Iran has started developing quantum technology, Salehi says. Tehran Times.
https://www.tehrantimes.com/news/457400/Iran-has-started-developing-quantum-
technology-Salehi-says
Salton, G., & Mcgill, M.J. Introduction to Modern Information Retrieval[M]. New York: McGraw-
Hill Book Copany, 1983.
Shibata, N., Kajikawa, Y., Takeda, Y., & Matsushima, K. (2008). Detecting emerging research
fronts based on topological measures in citation networks of scientific publications.
Technovation, 28(11), 758–775. https://doi.org/10.1016/j.technovation.2008.03.009
Small, H., Boyack, K.W., & Klavans, R. (2014). Identifying emerging topics in science and
technology. Research Policy, 43(8), 1450–1467. https://doi.org/10.1016/j.respol.2014.02.005
Small, H., & Upham, P. (2009). Citation structure of an emerging research area on the verge of
application. Scientometrics, 79(2), 365–375. https://doi.org/10.1007/s11192-009-0424-0
Smith-Goodson, P. (2019). Quantum USA Vs. Quantum China: The World’s Most Important
Technology Race. https://www.forbes.com/sites/moorinsights/2019/10/10/quantum-usa-vs-
quantum-china-the-worlds-most-important-technology-race/?sh=6f76589e72de
Tollefson, J. (2018). China declared world’s largest producer of scientific articles. Nature,
553(7689), 390–390. https://doi.org/10.1038/d41586-018-00927-4
Van Hooydonk, G. (1997). Fractional counting of multiauthored publications: Consequences for
the impact of authors. Journal of the American Society for Information Science, 48(10), 944–
945. https://doi.org/10.1002/(SICI)1097-4571(199710)48:10<944::AID-ASI8>3.0.CO;2-1
Wang, L.L., & Wang, X.W. (2017). Who sets up the bridge? Tracking scientific collaborations
between China and the European Union. Research Evaluation, 2. https://doi.org/10.1093/
reseval/rvx009
Wang, X.W., Xu, S.M., Wang, Z., Peng, L., & Wang, C.L. (2013). International scientific
collaboration of China: Collaborating countries, institutions and individuals. Scientometrics,
95(3), 885–894. https://doi.org/10.1007/s11192-012-0877-4
Wang, W.P. (2014). Study on the Patterns and Impacts of China’s International Scientific and
Technological Collaboration Based on Scientometrics. Doctoral dissertation, Beijing Institute
of Technology.
Zhang, Z.Q., Chen, Y.W., Tao, C., Xu, J., & TIAN, Q.F. (2018). Bibliometric Analysis on
International Competitive Situation of Quantum Information Research. WORLD SCI-TECH
R&D, 40(1), 37–49.
Zheng, J., Zhao, Z.Y., Zhang, X., Chen, D.Z., & Huang, M.H. (2014). International collaboration
development in nanotechnology: A perspective of patent network analysis. Scientometrics,
98(1), 683–702. https://doi.org/10/f5ns65
Zhou, P., & Glänzel, W. (2010). In-depth analysis on China’s international cooperation in science.
Scientometrics, 82(3), 597–612. https://doi.org/10.1007/s11192-010-0174-z
Zou, Y.W., & Laubichler, M.D. (2017). Measuring the contributions of Chinese scholars to the
research field of systems biology from 2005 to 2013. Scientometrics, 110(3), 1615–1631.
https://doi.org/10/f9vfz2
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Journal of Data and Information Science Vol. 7 No. 4, 2022
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Research Paper
Journal of Data and
Information Science
Appendix 1. The fundamental statistic of publications of zero citations.
Country Number of Papers Zero citation Papers Proportion
USA 40,906 2,224 5.44%
Peoples R China 40,180 4,876 12.14%
Germany 18,633 748 4.01%
England 11,904 441 3.70%
Japan 11,726 958 8.17%
Italy 8,937 492 5.51%
India 7,394 906 12.25%
Russia 6,252 721 11.53%
Brazil 3,520 316 8.98%
Iran 3,061 427 13.95%
Note: In the table the top five developed countries and the top five developing countries with the highest
number of papers are selected, by which the number of papers published is 152,513, accounting for 87.15% of
the total number of papers 175,002.
