Global Research Report
Multi-authorship andresearch analytics
Jonathan Adams, David Pendlebury,
Ross Potter and Martin Szomszor

Author biographies
Jonathan Adams is Director of theInstitute for Scientific Information,at the Web of Science Group.
He is also a Visiting Professor at King’s
College London, Policy Institute,and was awarded an Honorary
D.Sc. in 2017 by the Universityof Exeter, for his work in higher
education and research policy.
Ross Potter is a Data Scientist at theInstitute for Scientific Information.
He has extensive research experience
within academia, including NASArelated postdoctoral positions at
the Lunar and Planetary Institute,
Houston, Texas, and Brown University,
Providence, Rhode Island.

Martin Szomszor is Head of Research
Analytics at the Institute for Scientific
Information. He joined from Digital
Science where, as Chief Data Scientist
he applied his extensive knowledgeof machine learning, data integrationand visualization techniques tofound the Global Research Identifier
Database. He was named a 2015 top50 UK Information Age data leader
for his work in creating the REF2014
impact case studies database for
the Higher Education Funding
Council for England (HEFCE).

David Pendlebury is Head of
Research Analysis at the Institutefor Scientific Information, at the
Web of Science Group. Since 1983
he has used Web of Science data to
study the structure and dynamics ofresearch. He worked for many years
with ISI founder Eugene Garfield.
With Henry Small, David developed
ISI’s Essential Science Indicators.

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Today, as the ‘university’ of the
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are built. Our robust evaluation andcuration have been informed byresearch use and objective analysis
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Executive summary
The Web of Science has identified
a growing number of research
articles with 1,000 or moreunique authors across morethan 100 different countries.
The combination of many authors/
many countries creates a complex
authorship pattern that differsfrom more typical academic papers
and drives elevated citation rates.
In this report we describe twopatterns linking complex authorshipwith effects that increase citation
rates: a general increase associatedwith multi-authorship (more than
10 authors and more than fivecountries); and more perturbing
outcomes of hyper-authorship(more than 100 authors spread
across more than 30 countries).
Across the Web of Science, the mostfrequent number of authors on anarticle is three and 95% of global
output has 10 or fewer authors(Table 1). The most frequent numberof countries on an article is one and
99% of global output has authors
from five or fewer countries.
(Figure 1, Table 2)Complex authorship (many authors,
many countries) has continued to risein the last five years. The largest
relative increases are associated witha marked rise in hyper-authorship.
(Figure 2)
One additional country on anarticle has a greater benefit than
one additional author: complex
authorship is correlated withindicators of research performance(Category Normalized Citation
Impact - CNCI, Figure 3); author countis linked to a slight but continuous
impact rise (Figure 4); country countis linked to a steeper and more
erratic impact rise (Figure 5).

The effect of multi and hyperauthorship can be observed atcountry level. The effect depends
on the size of a country’s domestic
research base. For all countries,
citation impact increases with risingauthorship, but gains at higher
counts are more evident and variable
for smaller countries (Figure 8).
Every country gains citation impact
through its share of the 5% of global
multi-author 10 or more) articles.
In small and growing researcheconomies the average CNCI ofthese articles is five or more times
higher than typical articles (Table 3).

Author and impact patterns vary
between disciplines. In Biology,
rising author and country counts arecoherently linked to rising citation
impact, but in Clinical Medicine
the effect is more erratic for higher
counts with higher CNCI up to
100 times the world average.
In Chemistry there is no strong link
between author count and citations(Figure 6); Particle Physics has
erratically high impact values athigh country counts (Figure 7).

We recommend…
That the presence, in any sample, of articles with more than 10 authors should be acknowledged andseparately described because it will influence interpretation. Although multi-authorship leads to higher
impact, this link is coherent, progressive and regular for most (but not all) discipline categories and for somefields there is little or no effect. No change needs to be made to data management or analytics in this regard.
That articles with hyper-authorship, beyond 100 authors and/or 30 countries, be treated differently.
These articles are, to put it simply, different: they have unpredictable, incoherent effects that can sometimes bevery large. There is a strong argument for removing such data from all associated analyses at national as well as at
institutional level. Hyper-authorship produces particularly different and erratic patterns across Clinical Medicine
and Particle Physics. The effects do not fit into a broader pattern, are not repeated across all disciplines and arefar from consistent. The presence of such articles may be significant, even distorting, at institutional level.

3

Introduction
The Web of Science Group has long monitored the growth of author
and address counts on research publications.
In 2012, writing in ISI’s Science
Watch, Chris King noted that the
numbers of publications indexed on
Web of Science that had more than
50 authors rose from around 400 to
more than 1,000 between 1998 and2011, while the number with morethan 100 authors doubled to 600
over the same period (King, 2012).
Prior to 2000, the maximum numberof authors on a single article rarely
exceeded 500. In 2004 the 1,000 cap
was broken with a paper of 2,500
authors. The abundance of sucharticles continues to increase and therecord is now held by a 2015 article by
the ATLAS team on the Higgs Boson,with 5,153 authors at more than 500
institutional addresses (Aad et al.,2015; Mallapaty, 2018).
The count of countries listed amongauthor affiliations has similarly
increased. International collaboration
was relatively scarce in the 1980s but
has grown rapidly: more than half of
the articles attributable to any one
country now have a co-author fromanother (Adams, 2013). The incentives
for such collaboration are diverse;
data, however, can be a key driverand the growth of multinational
authorship is seen in both healthresearch and environmental science.
An article on human weight trends
has the most unique country authors
at 108 (more than half the membersof the UN) and more than 1,000
institutional addresses (NCD Risk
Factor Collaboration, 2017).
The reasons for, and benefits of,collaboration have been widely
studied (e.g. Katz and Martin, 1997;
Bozeman et al., 2013). The Economist(2016) reported on the rise of coauthorship and suggested that rising
article counts per author did not
represent increasing productivity.

4

It pointed to ‘guest authorship’and reciprocal offers of free author
tickets to colleagues as drivers thathave led to an actual drop in global
productivity of articles per author.
Rising author counts were noted
long ago by Derek De Solla Price(Price, 1963). Some may be driven
by a cultural habit of adding senior
members to research group outputs(Croll, 1984) which is said to be morecommon in some countries withrelatively hierarchical structures.
The increase in the number ofbiomedical papers that include a
departmental chair as co-author has
been noted (Drenth, 1998); however,
the increase in multi-authorship is too
widespread a phenomenon for thisto be a general explanation. There
are discipline analyses of authorship
cultures and patterns in specific areas,
including social sciences (Endersby,
1996), economics (Hudson, 1996)
and medically related researchwhere single authorship in the New
England Journal of Medicine fell
from 98% to 5% during the 20th
century (Constantian, 1999).
This rise in authorship counts
caused some concern (Cronin, 2001)
about what a name in an author list
meant in contemporary terms: is anauthor any longer synonymous witha writer? There are also questions of
where accountability and collective
responsibility lie as the authorshipof a paper rises (Croll, 1984):
is a paper with 100 authors the samekind of communication as a paperwith one or a few authors?
King (2012) reported the continuingrise in counts of papers with morethan 1,000 authors (termed hyperauthorship: Cronin, 2001).
These were concentrated in physics,
including work at international
space observatories and at CERN.

Cronin (2001) concluded that
hyper-authorship signifies a change
in research nature. The major
challenges of research – population
studies, epidemiology, climatechange, particle and space sciences –require investment in equipment,
data collection, longitudinalstudies and analytical processing
associated with large teams.
The lone researcher is now a lessviable model for major innovations.

Is a paper with
100 authors thesame kind ofcommunication
as a paper with
one or a few
authors?

Authorship poses three questions
for research analysts and policy
makers. The first is to document
and understand authorship changes
and to determine whether they are
discipline peculiarities or globally
pervasive. The second is whether
there is any relationship between
the academic impact of publications
and an increasingly large author count,
and whether the hyper-authoredpublications are in a category of theirown for analytical exercises.
The third, though not addressed
here, is the attribution of credit fora paper that has many authors(see Waltman and van Eck, 2015).

How many authors? How many countries?
To establish the general recent trend and current spread of authorship,
we looked at 15.7 million documents identified specifically as articles(not reviews or other document types) in journals indexed in
Web of Science over the period 2009-2018.
The earlier five-year period(2009-2013) contained 6.9 million
articles; the latter five years(2014-2018), 8.8 million.
As the academic literature has alreadyestablished, authorship is skewed;
most articles have a small number ofauthors with a few having an
exceptionally high number.
There are an additional 1,414 articles
with ‘zero’ authors; these are groupauthored with Agricultural Sciences
accounting for 60%.
The most common author count overthe period was three (Figure 1 – left).
More than 10 million articles (overtwo-thirds of the total) have fiveor fewer authors and 14.9 million(almost 95% of the total) have 10 or
fewer authors. This is an importantbackground statistic; while there is
no doubt that multi-authorship has
increased and that hyper-authorshipis now relatively frequent, the articles
produced by small author groups still
dominate the research literature.
The massively authored article
remains relatively scarce.
The distribution by countries(Figure 1 - right) also provides animportant reference point - themost common group, by far, is thatof articles on which all authors arefrom the same country. This may
seem surprising given the headlines
regarding the rise of international
collaboration.
However, while international networks
are common in Europe, our recent
G20 Scorecard showed that about
two-thirds of output from the USA andmore than three-quarters of China’s
output is domestic (Adams et al., 2019)with collaboration networks stilldeveloping in much of Asia andLatin America.

5

Figure 1 provides an important reality
check for multi-authorship: we need
to be careful about what we assume
is typical. There may be changes in
the pattern of authorship but there
is no evidence of disruptive shifts
in traditional patterns.
The next step is to look at the evidence
for recent change by comparing the
spread of authorship for the mostrecent five years (2014-2018) comparedto the five years before that (2009-2013)(Figure 2). Volume has increased
between the two periods.
For articles grouped by author count,that seems to result in a similar orderof magnitude increase across mostgroups, but there are two points ofinterest. First, the increase in countfor articles with 1-5 authors is small
compared to other groups suggestinga broad increase in multi-authorship.
Second, there is evidence of a shift
among the high (> 100) author counts
with similar numbers of articles in
the 100-500 and 500-1,000 authorgroups but a much greater increasein articles with over 1,000 authors.
For article authorship analyzed bycountry affiliation, the growth infrequency of authorship acrossnational boundaries is much clearer.
Counts in the groups up to 30
author-countries have increased
more, relative to the 1-5 countrygroup, whereas the group with
31-40 countries has become lessfrequent. Above 40 author-countries,
however, has grown dramatically.
In the period up to 2013, there were
only three articles with more than
50 author-countries; from 2014,
however, these groups havesignificant numbers of articles,with some containing morethan 100 country affiliations.

There has been agreat increase inarticles with over
1,000 authors

Figure 1.
The frequency of articles by count of authors (left) and by count of countries identified in author affiliations (right),
for 10 years (2009-2018) of Web of Science publication records. These results compare favourably to those ofWaltman and van Eck (2015).

12

2.5

10

Article count (millions)

Article count (millions)

2.0

1.5

1.0

0.5

8

6

4

2

0.0

0
0

2

4

6

8

10

0

2

Number of authors

4

6

8

10

Number of unique countries

Figure 2.
Changing profiles of authorship by unique individuals and by unique country addresses.
Data for articles indexed in Web of Science for 2009-2013 and 2014-2018.
Unique countries

107

107

106

106

105

105

2014–2018

Number of unique countries
2009–20132014–2018

+
101

81–
100

61–
80

60
51–

41–
50

40
31–

30
21–

11–
20

0

1+
100

–50

–10
501

101

21–

16–

6–1

2009–2013

00

100

0

100

51–
100

101

31–
50

101

30

102

20

102

11–
15

103

0

103

Number of authors

6

104

6–1

104

1–5

Article count

108

1–5

Article countAuthors108

Do all fields have multi-author publications?
The overall trend is clear:a relative growth in the numbersof multi-authored articles and asubstantial increase in the numbersof articles with authors from many
countries. Does this pattern extend
across all fields or is it limited to
specific research areas?
To explore this we assigned our
Web of Science data to the major
discipline categories in Web of
Science’s Essential Science Indicators(ESI). There are 21 categories
covering broad areas like Chemistry
and Physics plus a Multidisciplinary
category, covering journals like
Nature and Science (Table 1).
There are marked differences
between categories. The mostcommon authorship count remains
1-5 in most fields, but in thebiomedical categories – some ofwhich have more than one million
articles published over the 10-year
period – this has shifted towards
higher counts.
For example, in Clinical Medicine,
Microbiology and Molecular Biology
more than 10% of articles have morethan 10 authors and in Immunology
this is almost 20%. That contrasts withrelated areas such as Plant & Animal
Sciences where ~ 3% of articles
have authorship of 10 or more.
Physics and Space Science stand out
because they are categories where
low authorship counts remain common(respectively 74% and 66% of articles
with five or fewer authors) but where
those articles with hyper-authorshipare more abundant compared toother categories (0.6% and 1.5% withmore than 50 authors, respectively).

These patterns suggest different
research cultures between fields.
The biomedical sciences appear
to now commonly require large
teams whereas Physics is still rooted
in smaller, traditional teams while
also supporting work dependent
on massive ‘hyper’-collaboration.
The Social Sciences largely publish
with smaller authorship counts, but
so do Mathematics and Engineering.
In fact, the appearance of morethan 1% of Social Sciences articles
with authorship greater than 10 isperhaps something to watch as amarker of a shifting culture in an area
where the individual and the small
group have been the paradigm.

Table 1.
The relative frequency of author counts (shown as percentages within category) for articles indexedin Web of Science (2009-2018), grouped by Essential Science Indicators categories.
Count of articles
2009-18
184,499
316,589
387,710140,433
466,600
394,584
440,682
1,049,588
1,271,457
682,099
1,597,180
400,356
1,096,214
442,270
661,887
442,808
342,601
2,541,166
415,115
823,451
214,950
21,845

7

ESI category

Mathematics
Economics and Business
Computer Science
Social Sciences, general
Engineering
Psychiatry/Psychology
Geosciences
Physics
Environmental/Ecology
Plant and Animal Science
Chemistry
Agricultural Sciences
Space Science
Materials Science
Biology and Biochemistry
Neuroscience and Behavior
Pharmacology and Toxicology
Clinical Medicine
Microbiology
Molecular Biology and Genetics
Immunology
Multidisciplinary

Count of authors
1–5

6–10

11–15

16–20

21–30

31–50

51–100101–500 501–1000 1001–6000

99.2
98.8
90.8
90.0
87.6
79.6
74.9
74.0
71.6
69.5
67.5
66.9
66.3
65.6
53.9
50.9
50.4
48.7
47.3
42.1
34.0
62.1

0.8
1.1
8.7
8.7
11.6
17.5
21.7
21.5
25.2
27.4
29.8
30.4
20.4
31.5
38.2
39.0
41.6
40.2
42.2
40.7
46.3
28.1

0.0
0.1
0.4
1.0
0.6
2.2
2.4
2.8
2.4
2.6
2.2
2.0
5.7
2.6
6.4
7.8
6.8
8.3
8.4
11.7
14.6
7.0

0.0
0.0
0.1
0.2
0.1
0.4
0.5
0.6
0.4
0.3
0.3
0.4
2.5
0.2
1.0
1.5
0.9
1.9
1.5
3.1
3.4
1.7

0.0
0.0
0.0
0.1
0.0
0.2
0.3
0.3
0.2
0.1
0.1
0.3
2.3
0.0
0.3
0.6
0.3
0.8
0.5
1.5
1.3
0.8

0.0
0.0
0.1
0.3
0.1
0.5
0.12
0.18
0.09
0.03
0.04
0.03
1.37
0.00
0.09
0.19
0.05
0.20
0.11
0.59
0.31
0.29

0.00
0.00
0.00
0.01
0.00
0.02
0.03
0.13
0.03
0.01
0.01
0.01
0.80
0.00
0.02
0.05
0.01
0.04
0.02
0.20
0.05
0.07

0.000
0.000
0.001
0.004
0.000
0.005
0.005
0.221
0.007
0.003
0.007
0.001
0.650
0.000
0.007
0.010
0.004
0.012
0.002
0.092
0.016
0.023

0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.084
0.000
0.000
0.001
0.000
0.028
0.000
0.000
0.000
0.000
0.001
0.000
0.001
0.001
0.000

0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.084
0.000
0.000
0.001
0.000
0.028
0.000
0.000
0.000
0.000
0.001
0.000
0.001
0.001
0.000

Have all fields shown increasing
international collaboration?
It would be expected that themost frequent count of countriesof authorship would similarly
have increased.

It is also in accord with Adams andGurney (2018) who note that the
majority of international collaborations
are between two countries.

The data summarized in Table 2
may therefore be of some surprise as
the country counts are dominatedby the 1-5 country group, accounting
for around 99% of articles in all
categories except Immunology
and Space Science. This reflects
the extent to which the increasein the authorship count is driven
by collaboration between groups
rather than networks of individuals.

For example, just 1% of the UK’s
publications between 2002-2011
had co-authors from all of the USA,France and Germany (its mostfrequent partners). For the USA,the share of quadrilateral articles
with frequent partners is evenlower: around 0.1%.

That said, while the articles withmultiple country counts are scarcein themselves, their presence
across so many categories does
confirm Cronin’s (2001) view thatvery large global networks are
now an established part of research
management and publication output
in many disciplines, not just in Physics
and the biomedical categories.

Table 2.
Relative count of unique countries (shown as percentages within category) given as author affiliations on articles
indexed in Web of Science (2009-2018), grouped by Essential Science Indicators categories.
Count of articles
2009-18
184,499442,270
1,597,180
466,600
316,589
387,710400,356
661,887
140,433
342,601
394,584
682,099
415,115442,808
440,682
1,271,457
2,541,166
1,049,588
823,451
214,950
1,096,214
21,8458

ESI category

Mathematics
Materials Science
ChemistryEngineering
Economics and Business
Computer Science
Agricultural Sciences
Biology and BiochemistrySocial Sciences, general
Pharmacology and Toxicology
Psychiatry/Psychology
Plant and Animal Science
Microbiology
Neuroscience and Behavior
Geosciences
Environmental/Ecology
Clinical Medicine
Physics
Molecular Biology and Genetics
Immunology
Space Science
Multidisciplinary

Count of countries
1–5

6–10

11–20

21–30

31–40

41–100+

99.99
99.95
99.93
99.93
99.91
99.89
99.80
99.78
99.75
99.71
99.66
99.63
99.56
99.40
99.32
99.27
99.19
99.18
99.09
98.65
93.77
99.43

0.01
0.05
0.06
0.06
0.08
0.10
0.17
0.19
0.21
0.26
0.26
0.32
0.39
0.51
0.61
0.60
0.66
0.39
0.71
1.10
5.12
0.50

0.00
0.00
0.01
0.00
0.01
0.01
0.02
0.03
0.04
0.03
0.07
0.04
0.05
0.08
0.07
0.12
0.13
0.24
0.17
0.22
1.02
0.07

0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.01
0.01
0.00
0.00
0.01
0.01
0.01
0.02
0.02
0.08
0.00

0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.07
0.00
0.01
0.01
0.00

0.00000.00000.00180.00000.00000.00000.00020.00030.00120.00000.00000.00000.00000.00070.00110.00170.00250.10970.00020.00510.00070.0000How does author and country
collaboration affect citation rates?
Glanzel and Schubert (2004) identified
a link between international
collaboration and rising impact andWaltman and van Eck (2015: Figure 2)
drew attention to a rise in the average
citation impact for a journal article as
the authorship count increased. Ourdata confirm this broad pattern.
Both studies show that the effect ofadditional countries (up to aroundeight, in agreement with Adams andGurney, 2018) is much more marked
than additional authors (Figure 3).
The averages displayed in Figure 3
obviously hide a distribution of actual
citation impact values. Note that thevalues shown here are Category
Normalized Citation Impact (CNCI).

This is a conventional index used tonormalize citation counts because
counts rise over time at a rate that is
discipline dependent (see BOX 1).

Box 1.
Citation impact. The citation of an article by later publications is an indication of that article’s influence.
In science and technology disciplines, there is a correlation between citation counts and peer-review indicatorsof research significance. Citation counts rise over time at rates that are discipline dependent. Older publications
and life science publications are, on average, cited more often than recent papers in physical and social sciences.
To create a general index, the count for each article is ‘normalized’ against the average for that discipline category
in the same publication year. This is referred to as Category Normalized Citation Impact (CNCI). The benchmark
global average CNCI = 1.0

Figure 3.
The variation of Category Normalized Citation Impact (CNCI) related to the numbers of unique authors and uniquecountries identified in author affiliations. An additional country has a much greater effect on citation impact than an
additional author.

5

Mean CNCI

4

3

2

1

0
1

2

3

4

5

6

7

Number of authors or unique countries
Countries

9

Authors8

910

Box 2.
Boxplots. The analyses in Figure 4 (author counts) and Figure 5 (country counts) show the range of values for avariable while emphasising the core of the distribution. The coloured box spans the range between the upperand lower quartiles of the data distribution; the bar within it is the median for the range. The bar above the box
marks 1.5 times the interquartile range (following Tukey: see McGill et al., 1978) and the values beyond that arethen high outliers.
Figures 4 and 5 show the frequency distribution for the number of articles, in a bar chart, and CNCI (Category
Normalized Citation Impact), in a boxplot, for different groups of author and country numbers, respectively.

Overall, the data distribution insuccessive authorship groups appear
entirely coherent (Figure 4). There isno marked break-point between
historically typical articles and anyother group marked by greater
authorship. We would not, on thebasis of this analysis, point to any level

above which the density of authorshipmakes the publication functionally‘different’ for analytical purposes.
CNCI evidently does rise withauthor count. The average for eachsuccessive group slowly climbs toaround 30 authors after which there

is no marked average gain.
However, the upper value at 1.5
times the interquartile range does
continue to rise until around 50
authors. In fact, above 30 authors,
the boxplot limit values andranges are remarkably similar.

Figure 4.
The frequency distribution of grouped author counts across all categories (upper histogram) and the associated rangeof citation impact (CNCI) for each group (boxplot: see BOX 2)

ArticleArticle
countcount

107
107
106
106
105
105
104
104
103
103
1000

CNCICNCI

1000
100
100
10
10
1
1
0.1
0.1

1–5
1–5

6–10
6–10

11–15
11–15

16–20
16–20

21–30

31–50

Author number

21–30

31–50

Author number10

51–100101–500

501–1000

1001–6000

51–100101–500

501–1000

1001–6000

There are some notable outlier
values with extraordinarily high
CNCI (over 1,000 times the relevant
world average) in the 1-5 authorgroup. On preliminary inspection,
the most highly-cited of these are
identifiable as fundamental articles
on widely-used methods (e.g. clinicalpractice guidelines, crystal structurerefinement, image classification),but there may be cases wheresome other factor has comeinto play and this could emerge
on detailed analysis.
The CNCI data in successive countrycount groups (Figure 5) are relatively
coherent up to around 30 countries(although it is again noticeable thatin the 1-5 country group there are
extreme outliers with very high
CNCI), becoming increasingly erratic
in range and threshold values above

this value. The 31-40 group has lower
threshold values and range while the41-50 has several high outlier values.
The larger groups, based on verysmall publication numbers, have amore sharply rising average CNCI
up to the 100 country level. The lack ofclear coherence in this series suggeststhat there may be an argument for
excluding articles with high country
counts from standard analysis.
We will return to this point later.
Overall, the data, on average,
confirm the point made at Figure 3:
an additional country has a greater
effect on CNCI than an additional
author.

Impact rises
with authorshipbut the effectof additionalcountries isgreater thanthat of additional
authors

Figure 5.
The frequency distribution of grouped country counts (upper histogram) and the associated range of citation impact(CNCI) for each group (boxplot: see BOX 2)

107

ArticleArticle
count
count

107
106
106
105
105
104
104
103
103

1000
1000

CNCI
CNCI

100
100
10
10
1
1
0.1
0.1

1–5

6–10

11–20

21–30

1–5

6–10

11–20

21–30

31–40

41–50

Uniquenumber
31–40 country41–50
Unique country number

11

51–60

61–80

81–100

100+

51–60

61–80

81–100100+

Is there a greater citation effect in some fields?
The shifts in collaborative authorshipevidently vary by field. Table 1
showed that Plant & Animal Sciencemight be taken as a mid-tablereference category witha shift towards increased author

counts in the 6-10 range but with
about two-thirds of articles still
having five or fewer authors.
How does the variation in citation
impact for authors and for countries
compare with other categories?

Plant & Animal Science

And how do these patterns change
between the relatively broad
categories of the Essential Science
Indicators (ESI) and the finer level of
Web of Science journal categories?

Clinical Medicine

106
105

Article count

Article count

105
104
103
102

104
103
102
101

1000

100

CNCI

CNCI

100
10

1

10
1

0

10

01

–6

00

00

0

1–

10

50

50

10

1–

–1

00

0

0

–5

51

31

5

0

–3
21

–2
16

–1

10

106

105

105

Article count

Article count

11

5

106

104
103
102

104
103
102
101

101

100

1000

10

100

CNCI

CNCI

6–

1–

0
–6

01

Author number

10

Author number

00

00

0

10

50

1–
50

10

1–

–1

00

0

51

0

–5
31

5

0

–3
21

–2
16

–1
11

10
6–

1–

5

0.1

1

10

12

00

1–
20
0

10

Unique country number

81
–1

80
61
–

60
51
–

50
41
–

40
31
–

30
21
–

10

11
–2
0

6–

1–
5

1–
20
0

00

10

80

Unique country number

81
–1

61
–

60
51
–

50
41
–

40
31
–

30
21
–

11
–2
0

10
6–

1–
5

1

Figure 6.
The data illustrate the altering range of citation impact associated with changes in the frequency of authors andcountries for a selection of disciplines at the broad level Essential Science Indicators journal categories.
The CNCI rise in Plant & Animal Science is coherent and progressive with increasing author and country count.
Clinical Medicine clearly has a more extended scale at the upper ends of which CNCI variation becomes lesscoherent. Chemistry, by contrast, gains little CNCI with rising author count and almost none for additional countries
whilst Mathematics has an idiosyncratic pattern associated with generally low author counts. This confirms a diversityof author typology between major disciplinary areas. The more extreme authorship trends in Physics and Medicine are
not typical. This outcome is also important for analytical variations, such as fractional counting, which would have very
different consequences in, for example, Medicine and Chemistry.
Mathematics

106

105

105

104

Article count

Article countChemistry

104
103
102

103
102
101

101

1000

CNCI

100

10

104
103
102

0
00
–6

01
10

104

1–

0

105

Article count

105

00

0

Author number

106

10

50

50
0

10

1–

–1

00

0

0

–5

51

31

5

0

–3
21

–2
16

10

–1
11

5
1–

–6
01

10

6–

00

0

00

0

10

50

1–
50

10

1–

–1

00

0

51

0

–5
31

0

–3
21

–2
16

–1
11

1–

5

0.1

10

0.1

5

1

Author number

Article count

10

1

6–

CNCI

100

103
102
101

101

1000

100

CNCI

10

0
–2
0

10
1

Unique country number

81
–1
0

61
–8

0
51
–6

0
41
–5

0
31
–4

0
21
–3

0

–2
0
11

6–
1

00
1–
2

00
10

80

81
–1

61
–

60
51
–

50
41
–

40
31
–

30
21
–

0
11
–2

10
6–

1–
5

Unique country number

5

1

1

13

10

1–

CNCI

100

Figure 7.
The data illustrate the altering range of citation impact associated with changes in the frequency of authors andcountries for a selection of disciplines at the fine-grained level of the 257 Web of Science journal categories.
The CNCI rise for Biology, as in ESI Plant & Animal Science, is coherent and progressive with increasing author andcountry count. Genetics & Heredity generally looks similar but the spike in authorship over 500 is very clear:
the presence of one of these papers in a sample could be significant. Organic Chemistry is a truncated version of its
parent ESI Chemistry category. There is no CNCI gain from multi-authorship and international collaboration is rare.
By contrast, Physics, Particles & Fields has a spread of authorship and countries. However, whereas authorship counthas almost no effect, massively international articles boost CNCI substantially.

Genetics and Heredity, KM-WoS

105

105

104

104

Article count

Article count

Biology CU-WoS

103
102

103
102

101

101

100

100

1000

100

CNCI

CNCI

100
10

1

10
1

106

104

105

Article count

105

103
102

10

01

–6

00

0

00

0

103
102

100

101

100

1000

1

1–

104

101

10

10

50

50

10

1–

–1

00

0

0

–5

51

31

5

0

–3
21

–2
16

10

5

–1
11

6–

01

–6

00

1–

0

00

0
50

10

10

Author number

CNCI

Article countAuthor number

CNCI

1–
50

10

1–

–1

00

0

51

0

–5
31

5

0

–3
21

–2
16

–1
11

10
6–

1–

5

0.1

100
10
1

14

00

00

1–
2
10

Unique country number

81
–1

80
61
–

60
51
–

50
41
–

40
31
–

30
21
–

0

10

11
–2

6–

1–
5

00
1–
2

00
10

80

Unique country number

81
–1

61
–

60
51
–

50
41
–

40
31
–

30
21
–

0
11
–2

10
6–

1–
5

0.1

15

00

00

1–
2

10

Unique country number
0

00
00

–6

01

10

0

50

00

10

1–

50

1–

0

–5

–1

51

31

0

0

–3

21

–2

5

10

–1

11
16

10

Author number

81
–1

80

61
–

60

51
–

50

41
–

40

31
–

30

21
–

1

0

105

10

103
5

101

6–

1

1–

10

CNCI

Article count

102

11
–2

104

Article count

Article count
103

6–

10

CNCI

0

00

00

–6

01

10

0

50

10

1–

50

0

00

–1

1–

10

51

0

–5

31

5

0

–3

21

–2

16

–1

11

5

10

6–

1–

CNCI
105

1–
5

0

0

1–
20

10

Unique country number

–1
0

0

Article countAuthor number

81

–8

61

0

–6

51

0

–5

41

0

–4

31

0

–3

21

0

–2

11

6–
10

1–
5

CNCI

Chemistry, Organic EE-WoS
Physics, Particles and Fields, UP-WoS

105

104

104

103

100

100

10

1

0.1

105

104

103

102

102

101

100

10

1

Are some countries affected more than others?
For larger research economies,
illustrated by the UK and Germany,
sets of articles grouped by theincreasing authorship arereasonably large and the patternis broadly similar (Figure 8).
As authorship rises, average CNCI
also rises to a maximum around
50 authors, beyond which average
CNCI tends to fall slightly.

This pattern is not maintained
amongst a geographical spread ofother research economies. The profile
for categories beyond the 50-author
point may depend on the degreeof involvement in either, or both,of particle physics and medical
epidemiology. Bulgaria is linked into
the European Research Area and its
profile seems similar to Germany,

although there are relatively more
articles with low CNCI in the
categories where author count is
ten or fewer, until the 500-1,000 author
category when average citation
impact spikes upwards. That spikeis also seen in the data for theother examples shown.

Figure 8.
The national variation in author count and CNCI (see BOX 1) for a geographical spread of six larger and smaller
research economies. The data show the frequency of each grouped author counts across all research areas (upper
histogram) and the boxplot (see BOX 2) shows the associated range of citation impact (CNCI) for each group.
The triangles on the boxplots represent the mean.
UK

Germany

Article count

105

104

105

104

103

103

103

103

102

102

CNCI

CNCI

Article count

106

101
100

101
100

16

31
–5
0

21
–3
0

16
–2
0

11
–1
5

6–
10

51
–1
00
10
1–
50
0
50
1–
10
00
10
01
–6
00
0

Author number

1–
5

0
10
1–
50
0
50
1–
10
00
10
01
–6
00
0

–5
0

51
–1
0

31

–3
0
21

–2
0
16

11
–1
5

6–
10

1–
5

10–1

Author number

17

Author number

Author number

1–
50
0
50
1–
10
00
10
01
–6
00
0

10

100

51
–1
00

10

31
–5
0

102

21
–3
0

102

16
–2
0

Ethiopia
Author number

0

0

0

5

00

0

00

0

00
50
10
–6

01

10

1–

50

1–

10

–1

51

–5

–3
31

21

–2

16

–1

10

10

11

0

CNCI

102

6–

0

10

5

00

00

0

1

1–

–6

01

10

50

10

1–

50

1–

Article count

Article count

102

11
–1
5

103

Article countAuthor number
10

0

0

0

5

00

–5

31
–1

–3

21

51

–2

–1

10

5

16

11

6–

1–

CNCI
103

6–
10

1

CNCI

Article count
104

1–
5

1–
50
0
50
1–
10
00
10
01
–6
00
0

10

51
–1
00

31
–5
0

21
–3
0

16
–2
0

11
–1
5

10

6–
10

1–
5

CNCI

Bulgaria
Chile

104

103

102

102

101

10–1
100

Sri Lanka

104

103

102

103

102

101

–1

100

The small proportion of articles
with high author counts may attract
relatively high citation counts inmany categories, although the effectof this at national level is variable
since the average CNCI for sucharticles is not always greater thanthat for articles with lower author
counts. However, it is also evident
that articles with high counts ofcountries in author address affiliations
not only have high CNCI but that
this may be erratically different
from more conventional articles.
The effect of ‘outlier’ data points
inevitably becomes greater whensamples are smaller. Thus, forbibliometric analyses, this would
become most apparent for smaller
countries (as seen in Figure 8) andat institutional level. Such a possibility
was identified by Must (2014).
To test the effect of these highauthor/country count articles, weanalyzed the likely citation impact ofcountries if their portfolio focusedon the more frequent articles
with lower authorship counts.

In fact, 94.98% of global articles
published between 2009-18 had
10 authors or fewer, so we canlook at this group as the ‘typical’
95% of global low - perhaps better
described as normal - authorship.
The residual 5% of global articles
with higher multi-authorship thenform a second, comparator group.
For the large trans-Atlantic researcheconomies, the 5% high-author
count articles have around 2.5
times the CNCI of the 95% of more‘typical’ articles with ten or fewer
authors. These articles are about
10% of their output, because they
have the capacity to contributeto many highly collaborative
projects, and substantively raise
their average national CNCI.
China is different. Its multi-author
articles have twice the average CNCIof typical articles but they make up
only 5% of national output (about
75% of China’s publication output
is purely domestic) and so raise theoverall CNCI only marginally.

The smaller research economies areaffected much more than the larger.
The average CNCI of their ‘typical’
output is usually below world average.
The average CNCI of the multi-author
articles on which their researchers
appear is higher than for the larger
economies because they have few
domestic multi-author articles andco-author relatively more often on
multi-country publications. The effectof these articles is to raise their overall
CNCI significantly, usually putting
it above world average and in somecases doubling the headline figure.
The average CNCI for Sri Lanka
is 0.65 on the 7,436 articles withnormal authorship but almost 7.0 on
the ~1,000 multi-authored articles
raising the country’s overall average
CNCI above the UK and USA; it is
the highest of any country in Table 3.
It is essential to recognize, understandand describe this collaborative
multi-author effect in order tointerpret that headline average.

Table 3.
Count of journal articles (2009-2018) and average CNCI (see BOX 1) for four large and four smaller research economies.
Counts are shown for each country’s total articles, for the article count on which it has at least one author among the 95%of all global articles with authorship of ten or fewer, and for its count among the 5% of articles with greater authorship.
CNCI values are then shown for each sub-set of articles plus the CNCI ratio between the most authored 5% and least
authored 95% for that country. Green-red shows low-high values in each column.

Articles (2009-18)

Citation impact (CNCI)

Total

Low 95%High 5%Overall

For low 95%

For high 5%

Ratio high/low

USA

3,964,964

3,644,184

320,780

1.32

1.20

2.69

2.24

China

2,469,444

2,334,272

135,172

1.02

0.97

1.89

1.94

UK

1,148,033

1,028,160

119,873

1.42

1.23

3.08

2.51

Germany

1,044,111

920,866

123,245

1.25

1.05

2.73

2.59

Chile

79,25370,230

9,023

1.03

0.75

3.15

4.19

Bulgaria

29,11925,523

3,596

0.80

0.45

3.34

7.49

Ethiopia

13,287

12,185

1,102

1.18

0.77

5.66

7.31

Sri Lanka

8,519

7,436

1,083

1.46

0.65

6.96

10.63

18

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