PPOL 650 Issue Analysis Paper Instructions You will submit a paper analyzing an issue related to the intersection of international law, policy, politics, and diplomacy. Upon review of the course material and topics of study, you will select a topic based on concepts studied during the course. You must identify a major international crisis, provide a factual background, collect data describing the process used to resolve the crisis, explain whether the plan used was the best course of action, and explain the outcome. You are required to compare the effectiveness of the plan in light of all the international issues, identify the specific strengths and weaknesses of the approach, and note how diplomacy was used to address the crisis. You must also include a review of alternate plans that may have been effective in resolving the issue. The paper must include a minimum of 3–5 scholarly sources (ex. books or peer reviewed articles) formatted in current Turabian style. The assignment must be 5–7 pages. Your Issue Analysis Paper is due by 11:59 p.m. (ET) on Sunday of Module/Week 3. 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 immigra.

1. PPOL 650
Issue Analysis Paper Instructions
You will submit a paper analyzing an issue related to the
intersection of international law, policy, politics, and
diplomacy. Upon review of the course material and topics of
study, you will select a topic based on concepts studied during
the course. You must identify a major international crisis,
provide a factual background, collect data describing the
process used to resolve the crisis, explain whether the plan used
was the best course of action, and explain the outcome. You are
required to compare the effectiveness of the plan in light of all
the international issues, identify the specific strengths and
weaknesses of the approach, and note how diplomacy was used
to address the crisis. You must also include a review of
alternate plans that may have been effective in resolving the
issue. The paper must include a minimum of 3–5 scholarly
sources (ex. books or peer reviewed articles) formatted in
current Turabian style. The assignment must be 5–7 pages.
Your Issue Analysis Paper is due by 11:59 p.m. (ET) on Sunday
of Module/Week 3.
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

2. 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

3. 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.
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

4. 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
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.

5. 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
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. 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
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

7. 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
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

8. 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
……
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

9. 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.
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
[1] .Xu, B.M., X.G. Ni. Development Trend and Key Technical
Progress of

10. Cloud Computing[J]. Bulletin of the Chinese Academy of
Sciences,
2015. 30(2), pp. 170-180.
[2] Xiao, Y., Y. Cheng, Y.J. Fang, Research on Cloud
Computing and Its
Application in Big Data Processing of Railway Passenger Flow,
in
Iaeds15: International Conference in Applied Engineering and
Management, P. Ren, Y. Li, and H. Song, Editors. 2015, Aidic
Servizi
Srl: Milano. pp. 325-330.
[3] Zhu, Y.Q., P. Luo, Y.Y. Huo et. al, Study on Impact and
Reform of Big
Data on Higher Education in China, in 2015 3rd International
Conference on Social Science and Humanity, G. Lee and Y. Wu,
Editors. 2015, Information Engineering Research Inst, USA:
Newark. p.
155-161.
[4] Wang, X., L.C. Song, G.F. Wang et.al. Operational Climate
Prediction
in the Era of Big Data in China: Reviews and Prospects[J].
Journal of
Meteorological Research, 2016. 30(3), pp. 444-456.
[5] Dahlman, C., L. Westphal, Technological effort in industrial
development——An Interpretative Survey of Recent
Research[R]. 1982.
[6] Cerna, L., M. Czaika, European Policies to Attract Talent:
The Crisis
and Highly Skilled Migration Policy Changes, in High-Skill
Migration
and Recession. 2016, Springer. pp. 22-43.

11. [7] Jin, X., B.W. Wah, X. Cheng et. al. Significance and
challenges of big
data research[J]. Big Data Research, 2015. 2(2), pp. 59-64.
[8] Fang, H., Z. Zhang, C.J. Wang et. al. A survey of big data
research[J].
IEEE Network, 2015. 29(5), pp. 6-9.
[9] Cole, F.J., Eales, N. B. The history of comparative
anatomy[J]. science
Progress, 1917. 11, pp. 578-596.
[10] Gallardo-Gallardo, E., S. Nijs, N. Dries et. al. Towards an
understanding
of talent management as a phenomenon-driven field using
bibliometric
and content analysis[J]. Human Resource Management Review,
2015.
25, pp. 264-279.
[11] Clarke, B.L. Multiple authorship trends in scientific
papers[J]. Science,
1964. 143(3608), pp. 822-824.
[12] Gonzalez-Valiente, C.L., J. Pacheco-Mendoza, R.
Arencibia-Jorge. A
review of altmetrics as an emerging discipline for research
evaluation[J].
Learned Publishing, 2016. 29(4), pp. 229-238.
2017 Proceedings of PICMET '17: Technology Management for
Interconnected World
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/NLD (Gebruik deze instellingen om Adobe PDF-documenten
te maken waarmee zakelijke documenten betrouwbaar kunnen
worden weergegeven en afgedrukt. De gemaakte PDF-
documenten kunnen worden geopend met Acrobat en Adobe
Reader 5.0 en hoger.)
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/ENU (Use these settings to create PDFs that match the
"Required" settings for PDF Specification 4.01)
>>
>> setdistillerparams
<<

22. /HWResolution [600 600]
/PageSize [612.000 792.000]
>> setpagedevice
PPOL 650
Issue Analysis Paper Grading Rubric
Student:
Criteria
Novice
Competent
Proficient
Formatting
0–1 points
· Current Turabian guidelines are followed with frequent errors,
or not followed.
· Less than 1 typed page.
· Any of the following are not present: typed, 12-pt. font, Times
New Roman, double spaced, 1-inch margins.
2–3 points
· Current Turabian guidelines are followed with few errors.
· Less than 3 pages.
· Typed, 12-pt. font, Times New Roman, double spaced, 1-inch
margins.
4–5 points
· Current Turabian guidelines are followed.
· Length of 3–5 pages.
· Typed, 12-pt. font, Times New Roman, double spaced, 1-inch
margins.
Spelling and Grammar
0–14 points
· Continuous grammatical and spelling errors.
15–16 points
· Some grammatical and spelling errors.
17–20 points

23. · Minimal or no grammatical and spelling errors.
Content
0–49 points
· Major points are not clear, nor are they given sufficient
support.
· A major international crisis is not identified, background is
not provided, and analysis about the outcome of the crisis is
missing.
· An evaluation of the approach and discussion of relevant plans
is missing.
50–52 points
· Major points are clearly articulated, but not sufficiently
supported.
· A major international crisis is identified, but background is
not provided or partially provided, and partial analysis about
the outcome of the crisis is provided.
· An evaluation of the approach and discussion of relevant plans
is partially included.
53–60 points
· Major points are clearly articulated and sufficiently supported.
· A major international crisis is identified, background is
provided, and full analysis about the outcome of the crisis is
provided.
· An evaluation of the approach and discussion of relevant plans
is included.
References
0–9 points
· No scholarly references are present.
10–11 points
· Less than 1–2 scholarly references are present and
appropriately integrated.
12–15 points
· 3–5 scholarly references are present, clearly demonstrated,
and appropriately integrated.
Total:
/100