Analysis on the Demand of Top Talent Introduction in Big Data and Cloud Computing Field in China Based on 3-F Method Zhao Linjia, Huang Yuanxi, Wang Yinqiu, Liu Jia National Academy of Innovation Strategy, China Association for Science and Technology, Beijing, P.R.China Abstract—Big data and cloud computing, which can help China to implement innovation-driven development strategy and promote industrial transformation and upgrading, is a new and emerging industrial field in China. Educated, productive and healthy workforces are necessary factor to develop big data and cloud computing industry, especially top talents are essential. Therefore, a three-step method named 3-F has been introduced to help describing the distribution of top talents globally and making decision whether they are needed in China. The 3-F method relies on calculating the brain gain index to analysis the top talent introduction demand of a country. Firstly, Focus on the high-frequency keywords of a specific field by retrieving the highly cited papers. Secondly, using those keywords to Find out the top talents of this specific field in the Web of Science. Finally, Figure out the brain gain index to estimate whether a country need to introduce top talents of a specific field abroad. The result showed that the brain gain index value of China's big data and cloud computing field was 2.61, which means China need to introduce top talents abroad. Besides P. R. China, those top talents mainly distributed in the United States, the United Kingdom, Germany, Netherlands and France. I. INTRODUCTION Big data and cloud computing is a new and emerging industrial field[1], and increasing widely used in China[2-4]. Talents’ experience is a source of technological mastery[5], essentially for developing and using big data technologies. Most European states consider the immigration of foreign workers as an important factor to decelerate the decline of national workforces[6]. Lots of universities and research institutes have set up undergraduate and/or postgraduate courses on data analytics for cultivating talents[7]. EMC corporation think that vision, talent, and technology are necessary elements to providing solutions to big data management and analysis, insuring the big data success[8]. Bibliometrics research has appeared as early as 1917[9], and has been proved an effective method for assessing or identifying talents. Based on analyses of publication volume, journals and their impact factors, most cited articles and authors, preferred methods, and represented countries, Gallardo-Gallardo et. al[10] assess whether talent management should be approached as an embryonic, growth, or mature phenomenon. In this paper, we intend to analysis whether China need to introduce top talents in the field of big data and cloud computing by using bibliometrics. In section 2, the 3-F method for top talent introduction demand analysis will be dis.

1. Analysis on the Demand of Top Talent Introduction
in Big Data and Cloud Computing Field in China
Based on 3-F Method
Zhao Linjia, Huang Yuanxi, Wang Yinqiu, Liu Jia
National Academy of Innovation Strategy, China Association
for Science and Technology, Beijing, P.R.China
Abstract—Big data and cloud computing, which can help
China to implement innovation-driven development strategy and
promote industrial transformation and upgrading, is a new and
emerging industrial field in China. Educated, productive and
healthy workforces are necessary factor to develop big data and
cloud computing industry, especially top talents are essential.
Therefore, a three-step method named 3-F has been introduced
to help describing the distribution of top talents globally and
making decision whether they are needed in China. The 3-F
method relies on calculating the brain gain index to analysis the
top talent introduction demand of a country. Firstly, Focus on
the
high-frequency keywords of a specific field by retrieving the
highly cited papers. Secondly, using those keywords to Find out
the top talents of this specific field in the Web of Science.
Finally,
Figure out the brain gain index to estimate whether a country
need to introduce top talents of a specific field abroad. The
result
showed that the brain gain index value of China's big data and
cloud computing field was 2.61, which means China need to

2. introduce top talents abroad. Besides P. R. China, those top
talents mainly distributed in the United States, the United
Kingdom, Germany, Netherlands and France.
I. INTRODUCTION
Big data and cloud computing is a new and emerging
industrial field[1], and increasing widely used in China[2-4].
Talents’ experience is a source of technological mastery[5],
essentially for developing and using big data technologies.
Most European states consider the immigration of foreign
workers as an important factor to decelerate the decline of
national workforces[6]. Lots of universities and research
institutes have set up undergraduate and/or postgraduate
courses on data analytics for cultivating talents[7]. EMC
corporation think that vision, talent, and technology are
necessary elements to providing solutions to big data
management and analysis, insuring the big data success[8].
Bibliometrics research has appeared as early as 1917[9],
and has been proved an effective method for assessing or
identifying talents. Based on analyses of publication volume,
journals and their impact factors, most cited articles and
authors, preferred methods, and represented countries,
Gallardo-Gallardo et. al[10] assess whether talent management
should be approached as an embryonic, growth, or mature
phenomenon.
In this paper, we intend to analysis whether China need to
introduce top talents in the field of big data and cloud
computing by using bibliometrics. In section 2, the 3-F method
for top talent introduction demand analysis will be discussed.
In section 3, we will analysis the demand of top talent
introduction in big data and cloud computing field in China.

3. II. METHOD
In general, metering indicators contain the most productive
authors, journals, institutions, and countries, and the
collaboration networks between authors and institutions[11,
12]. Based on the commonly used bibliometrics method, 3-F
method for top talent introduction demand analysis is proposed.
3-F method has three steps:
Firstly, searching the literature database and forming a
high-impact literature collection in a specific field. Focusing on
the high-frequency keywords in the high-impact literature
collection by using the text analysis method as the research
hotspots. Just to be clear, the high-impact literature refers to the
journal literature whose number of cited papers ranked in the
top 1% in the same discipline and in the same year.
Secondly, retrieving those keywords in the Web of Science
to find out where those top talents of this specific field are.
Find the top talents by collected the information about talents’
country distribution, the institutions distribution and so on
through the high-impact literature collection. Among them, the
top talent refers to the first author or the communication author
of the high-impact literatures.
Finlly, Figure out the brain gain index to determine the top
talents introduction demand of a certain country. The brain gain
index is calculated as following formulas:
Iik = (Twk / Tik) / (Pw / Pi) (1)
Among them, Iik means the brain gain index value of
country (i) in the field (k), Twk means the number of world’s
top
talents in the field (k), Tik means the number of country’s (i)
top

4. talents in the field (k), Pw means the world population, Pi
means the country’s (i) population. If Iik was more than 1, that
means the country (i) has less top talents in the field (k),
therefore the talent introduction demand will be relatively
strong. In contrast, if Iik was less than 1, that means the
country’s (i) has greater top talents in the field (k) than the
world average, and the talent introduction demand will not be
so strong.
Additionally, the literature information mainly from the ISI
Web of Science (SCI, CPCI-S), and the the data analysis and
visualization tools are TDA and Tableau.
2017 Proceedings of PICMET '17: Technology Management for
Interconnected World
978-1-890843-36-6 ©2017 PICMET
III. CASE STUDY
Using 3-F method to analysis the top talents introduction
demand in the big data and cloud computing field. We
collected the high-impact literatures from January 1, 2006 to
July 31, 2016. The literature Language was English and the
literature type was article. Combining with the above
conditions, we got 546 high-impact literatures in the big data
and cloud computing field. Then the high-frequency keywords
have been obtained (Table 1) and served as the research
hotspots set.
TABLE I. THE RESEARCH HOTSPOTS OF THE HIGH-
IMPACT LITERATURES IN
BIG DATA AND CLOUD COMPUTING FIELD

5. Order Keywords Frequency
1 cloud computing 48
2 big data 24
3 virtualization 11
4 cloud manufacturing 9
5 internet of things (IoT) 8
6 mobile cloud computing 8
7 bioinformatics 6
8 climate change 6
9 Hadoop 6
10 software-defined networking (SDN) 6
……
At the same time, we displayed the frequency distribution
of research hotspots in the way of cloud chart(fig. 1).
Fig. 1. The cloud chart of research hotspots that in the field of
big data and
cloud computing
Then, we find the information about nationality (Table 2),
institutes (Table 3) of top talents in the high-impact literature

6. collection. Results showed there were 662 top talents
worldwide in the big data and cloud computing field. The top
ten countries or regions who had the most top talents were the
United States, P.R.China, the United Kindom, Germany, the
Netherlands, France, Canada, Australia, Italy and Switzerland
and Spain tied for the tenth.
TABLE II. THE NATIONALITY DISTRIBUTION OF TOP
TALENTS IN THE BIG
DATA AND CLOUD COMPUTING FIELD
Order Country or Region Number of the top talent
1 US 268
2 P. R. China 48
3 UK 47
4 Germany 39
5 Netherlands 28
6 France 27
7 Canada 22
8 Australia 21
9 Italy 19
10 Switzerland 13
Spain 13
12 Japan 10
13 Korea 8
Malaysia 8
15 Singapore 7
New Zealand 7
17 Austria 6
18 Belgium 5
Sweden 5
India 5
Chinese Taipei 5
……
TABLE III. THE INSTITUTES DISTRIBUTION OF TOP

7. TALENTS IN THE BIG
DATA AND CLOUD COMPUTING FIELD
Order Country or Region Number of the top talent
1 Harvard University (US) 10
2 Purdue University (US) 7
University of Malaya (Malaysia) 7
University of Maryland (US) 7
Unversity of Melbourne (Australia) 7
University of Missouri (US) 7
7 Oxford Unversity (UK) 6
8 Chinese Academy of Sciences (P.R.China) 5
ETH Zurich (Switzerland) 5
Massachusetts General Hospital (US) 5
Northwestern University (US) 5
University of British Columbia (Canada) 5
UC, Berkeley (US) 5
UC, San Diego (US) 5
University of Texas at Austin (US) 5
University of Washington (US) 5

8. ……
2017 Proceedings of PICMET '17: Technology Management for
Interconnected World
From table 2 and 3 we can see that China was in the second
place worldwide. However, China's top talent is much less than
the United States. In addition, the overall strength of Chinese
research institutions is not strong. So, whether China should
introduce top talents from other countries is need to be
discussed.
According to the formula of the brain gain index, and using
the world population data as well as the Chinese mainland
population data released by the World Bank, the value of the
Chinese brain gain index of big data and cloud computing was
2.61. In comparison, the brain gain index value of the United
States was 0.11. That means China need to introduce top talent
in the field of big data and cloud computing.
IV. CONCLUSION
In the knowledge economy era, the international flow of top
talent has become convenient and frequent. Facing the world's
top talent shortage, China and the world's major countries have
developed overseas top talent introduction programs. Until
2007, almost all European countries had introduced some
skillselective migration policies in order to attract the top
talents. To make the overseas top talent introduction programs
more effective and targeted is helpful for occupying the
strategic high ground in the global top talent competition.

9. This paper improved the traditional talent evaluation
function of bibliometric method, and presented the 3-F analysis
method, which was applied to analyze the demand of top
talents. The 3F method could help the government official to
make decision whether need to introduce top talents to develop
a new industry field and lock these top talents geographic
location.
REFERENCES
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2017 Proceedings of PICMET '17: Technology Management for
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073006e0069006e00670020006f00670020007500740073006b00
7200690066007400200061007600200066006f007200720065007
4006e0069006e006700730064006f006b0075006d0065006e0074
00650072002e0020005000440046002d0064006f006b0075006d0
065006e00740065006e00650020006b0061006e002000e5007000
6e00650073002000690020004100630072006f006200610074002
00065006c006c00650072002000410064006f0062006500200052
0065006100640065007200200035002e003000200065006c006c0
0650072002e>
/PTB
<FEFF005500740069006c0069007a00650020006500730073006
1007300200063006f006e00660069006700750072006100e700f5
0065007300200064006500200066006f0072006d0061002000610
0200063007200690061007200200064006f00630075006d006500
6e0074006f0073002000410064006f00620065002000500044004
600200061006400650071007500610064006f0073002000700061
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650073007300e3006f00200063006f006e0066006900e10076006
50069007300200064006500200064006f00630075006d0065006e
0074006f007300200063006f006d0065007200630069006100690
073002e0020004f007300200064006f00630075006d0065006e00

20. 74006f00730020005000440046002000630072006900610064006
f007300200070006f00640065006d002000730065007200200061
0062006500720074006f007300200063006f006d0020006f00200
04100630072006f006200610074002000650020006f0020004100
64006f00620065002000520065006100640065007200200035002
e0030002000650020007600650072007300f50065007300200070
006f00730074006500720069006f007200650073002e>
/SUO
<FEFF004b00e40079007400e40020006e00e40069007400e4002
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006e0020006c0075006f0074002000410064006f0062006500200
050004400460020002d0064006f006b0075006d0065006e007400
740065006a0061002c0020006a006f0074006b006100200073006
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1002000740075006c006f007300740061006d0069007300650065
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02d0064006f006b0075006d0065006e0074006900740020007600
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0200035002e0030003a006c006c00610020006a00610020007500
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/SVE
<FEFF0041006e007600e4006e00640020006400650020006800e
4007200200069006e0073007400e4006c006c006e0069006e0067
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650020005000440046002d0064006f006b0075006d0065006e007
400200073006f006d002000700061007300730061007200200066
00f60072002000740069006c006c006600f60072006c006900740
06c006900670020007600690073006e0069006e00670020006f00
6300680020007500740073006b007200690066007400650072002
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21. 006d0065006e0074002e002000200053006b00610070006100640
0650020005000440046002d0064006f006b0075006d0065006e00
740020006b0061006e002000f600700070006e006100730020006
90020004100630072006f0062006100740020006f006300680020
00410064006f00620065002000520065006100640065007200200
035002e00300020006f00630068002000730065006e0061007200
65002e>
/ENU (Use these settings to create PDFs that match the
"Required" settings for PDF Specification 4.01)
>>
>> setdistillerparams
<<
/HWResolution [600 600]
/PageSize [612.000 792.000]
>> setpagedevice