Semantic Big Data Analyses (PVM) used to check on the perception of Germany in the USA; Nina Smidt, Torsten Oltmanns, Ivo Hajnal, AmCham Germany

1. Best Friends Forever?
How the US thinks and feels about Germany
AmCham Germany
Dr. Nina Smidt
Berlin, June 25, 2018

2. The Task
1
> Working assumption: Germany has lost relevance in the United States.
> The “Germany Year USA 2018/2019” undertaken by the German Foreign Office and partners is an
effort to counteract this and strengthen ties.
> Question: What can Germany do, and how can transatlantic institutions help, to improve
perceptions of Germany in the US?

3. First-ever Perception Value Management (PVM)TM analysis on the perception of a country
Topline findings:
> A mismatch between general public opinion (big data analysis) and expert opinion
(survey of transatlantic experts);
> Perception of Germany’s performance in the world is strong, but that is not always positive – seen
as a threatening power;
> Perception on “Character” and “Sympathy” values is low.
2* PVM –semantic big data analytics developed by Prof. Ivo Hajnal and Prof. Torsten Oltmanns

4. Big Data
Analysis
Step 1 Step 2 Step 3 Step 4
Public perceptions
reflected in social, online
and print media
> Twitter analysis over
one year (September
1, 2016 – September
1, 2017)
> 25 most prominent
print and online US
media outlets
> Standard Risk
Analysis and
specified PVM
Analysis
Evaluation and
Comparison
Recommendations
Online stakeholder
survey with a select
group of 25 transatlantic
experts from the policy,
business and think tank
sectors. Equal parts US/
German citizens.
Recommendations for
an advanced
communication strategy
to help strengthen the
perception of Germany
in the United States and
support transatlantic ties.
Stakeholder
Survey
> Analysis of findings
using Perception
Value Management
MatrixTM.
> Comparison of Big
Data Analysis and
Stakeholder Survey
Results.
3* PVM –semantic big data analytics developed by Prof. Ivo Hajnal and Prof. Torsten Oltmanns

5. Semantic Big Data Analytics: Twitter Analysis
Step 1: Analysis
Data made available by Twitter Analytics; data refers to total amount of
tweets with search criteria
4

6. Semantic Big Data Analytics: Twitter Analysis
Step 1: Analysis
Data made available by Twitter Analytics; data refers to total
amount of tweets with search criteria
5

7. Semantic Big Data Analytics: Twitter Analysis
Step 1: Analysis
Data made available by Twitter Analytics; data refers to total
amount of tweets with search criteria
6

8. Semantic Big Data Analytics: Twitter Analysis
Step 1: Analysis
Data made available by Twitter Analytics; data refers to total
amount of tweets with search criteria
7

9. Semantic Big Data Analytics: Media outlets
Step 1: Analysis
1. USA Today
2. The New York Times
3. The Wall Street Journal
4. The Los Angeles Times
5. The Washington Post
6. New York Daily News
7. The San Francisco Chronicle
8. The New York Post
9. The Chicago Tribune
10. The Star-Ledger
11. The San Jose Mercury News, Contra
Costa Times and The Oakland Tribune
12. Chicago Sun-Times
13. Philadelphia Inquirer and Philadelphia
Daily News
14. The Houston Chronicle
15. The Dallas Morning News
16. Seattle Times
17. The Arizona Republic
18. The StarTribune
19. The Denver Post
20. The Plain Dealer
21. The Oregonian
22. The Detroit Free Press
23. The Tampa Tribune
24. Newsday
25. San Diego Union-Tribune
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10. Semantic Big Data Analytics: Perception Value Management Matrix
9
Step 1: Analysis
Key tenets:
> Measures general sentiment and attitude towards Germany;
> Measures particular perception on “Performance,” Sympathy”
and “Character”;
> Evaluates a large segment of data from print and online media,
social media, websites and blogs;
> Measures perception criteria based on over 200 selectors;
> Focuses on main traditional news and social media outlets in
the US;
> Allows for a short-term prognosis regarding trends, challenges
and potential crisis situations;
> Evaluation of results is based on the Perception Value
Management Concept;
> Results are used to design an integrated communication
strategy that will strengthen Germany’s perception in the US;
> The matrix has been used in corporate analysis but not in
“nation-branding” (use of corporate marketing techniques by
countries to enhance international reputation).

11. Perception Value Triangle (PVMTM)
1. Performance (strengthens authority) – “Logos”
a. Cognition: Is the problem understood?
b. Competence: Are the required skills for problem
solving available?
c. Reflection: Who are responsible leaders / acting
parties?
2. Sympathy (builds coalition) – “Pathos”
a. Commonalities: What are the common points of view?
b. Openness: Is there respect and tolerance for other
opinions?
c. Interaction: Are there opportunities for cooperation
and exchange?
3. Character (establishes trust) – “Ethos”
a. Legibility: Identifying positions and values
b. Integrity: Understanding deeper motives
c. Consistency: Establishing reliability
10* PVM –semantic big data analytics developed by Prof. Ivo Hajnal and Prof. Torsten Oltmanns

12. 11
Step 1: Analysis
Multiplying Factors for Risk Analysis and PVM Calculation
General psychological selectors for Risk and PVM-Analysis
Data: Nina Smidt, 2017
Sample Total Lexicon Factor
up to 100%
Factor for General
Lexicon
Total Impact Factor
Risk Print:
Media USA
72% ≈ 1,4 ≈ 8 11,2
Risk Twitter:
Twitter USA
52% ≈ 2 ≈ 8 16
PVM Print:
Medien USA
5% ≈ 20 – 20
PVM Twitter:
Twitter USA
2,8% ≈ 35 – 35

13. Positive Emotions
Negative Emotions
Anxiety
Anger
Sadness
-25 -22.5 -20 -17.5 -15 -12.5 -10 -7.5 -5 -2.5 0 2.5 5 7.5 10 12.5 15 17.5 20 22.5 25 27.5 30
Bad feelings cancel out good feelings.
Print and Online Media USA (September 2016 - September 2017); Search Criteria: “Germany“, “Merkel“
Step 1: Analysis
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Data: Nina Smidt, 2017

14. Discrepancy
Difference
Implementation Skills
Power
0 2.5 5 7.5 10 12.5 15 17.5 20 22.5 25 27.5 30 32.5 35 37.5 40 42.5 45 47.5 50 52.5 55 57.5 60
Germany is a powerhouse; is that good?
Print and Online Media USA (September 2016 - September 2017; Search Criteria: “Germany“, “Merkel“)
Step 1: Analysis
Data: Nina Smidt, 2017
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15. Positive Emotions
Negative Emotions
Anxiety
Anger
Sadness
-45.00 -40.00 -35.00 -30.00 -25.00 -20.00 -15.00 -10.00 -5.00 0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00
Row 1/2: USA total 17/16
Row 3/4: Texas 17/16
Row 5/6: New York 17/16
Twitter captures strong negative emotions. Texas is harsher than New York.
Twitter (September 2016 - September 2017; Search Criteria: “Germany“, “Merkel“)
Step 1: Analysis
14
Data: Nina Smidt, 2017

16. Discrepancy
Difference
Implementation Skills
Power
0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 40.00 45.00 50.00 55.00
Row 1/2: USA total 17/16
Row 3/4: Texas 17/16
Row 5/6: New York 17/16
Germany is viewed as a power both on Twitter and in news media.
Twitter (September 2016 - September 2017); Search Criteria: “Germany“, “Merkel“
Step 1: Analysis
15
Data: Nina Smidt, 2017

17. Step 1: Analysis
PVMTM-Values in journalistic media show a deficit on “sympathy“
Media
9/16-9/17
Dangerous
Be aware
No concern
7,2
10,0
4,4
1,03,4
9,0
-9,2
-7,00
-5,4
-7,2
7,2
4,5
PVMTM Analysis Media, online and print
Data: Nina Smidt, 2017;
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* PVM –semantic big data analytics developed by Prof. Ivo Hajnal and Prof. Torsten Oltmanns

18. 17
PVMTM-Values on Twitter (USA total) show a more critical image than journalistic media
Twitter
9/16-9/17
Dangerous
Be aware
No concern
3,2
6,7
5,6
-0,74,2
6,3
-15,4
-8,4
-3,5
-9,1
5,2
3,3
PVMTM Analysis Twitter USA
Step 1: Analysis
Data: Nina Smidt, 2017 * PVM –semantic big data analytics developed by Prof. Ivo Hajnal and Prof. Torsten Oltmanns

19. Interim Results – 1
Translate findings into PVMTM Analysis
> Performance value – strong, but also seen as threat;
> Character value – weak, underdeveloped;
> Sympathy value – almost undetectable.
Interim Results
18* PVM –semantic big data analytics developed by Prof. Ivo Hajnal and Prof. Torsten Oltmanns

20. Stakeholder Survey: Germany and Merkel are perceived positively …
Strengths
Step 2: Stakeholder Survey
Data: Nina Smidt, 2017
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21. … but problems are apparent.
Weaknesses
Step 2: Stakeholder Survey
Data: Nina Smidt, 2017
20

22. Overall relations are strong, or at least normal …
Opportunities
Step 2: Stakeholder Survey
Data: Nina Smidt, 2017
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23. … but Germany cannot be complacent.
Threats
Step 2: Stakeholder Survey
Data: Nina Smidt, 2017
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24. Interim Results – 2
Mismatch between Big Data Analysis and Stakeholder Survey.
Interim Results
23
There is a mismatch between the big data analysis (representing a wide US audience) and the survey of a
select group of transatlantic experts:
> Topics that the select group considers important (economy, trade, NATO, EU leadership) are not the
ones reflected in big data (Merkel, Trump, Nazi history, far-right parties in Germany).
> Big data analysis and survey agree: Germany is strong on “Performance”.
> However, ”Performance” is viewed positively by survey group and negatively by wider US population.
> “Sympathy” related values do not occur at all in big data analysis: Friendship, Fun, Sports, Music,
Culture.
> Mismatch becomes even more apparent in the comparison of New York as a blue state and Texas as a
red state.

25. SWOT Analysis
Step 3: Evaluation and Comparison
Strength
Germany perceived as strong in
performance
Weakness
Germany is weak in character and
sympathy
Threat
Strong performance viewed as
threatening
Opportunity
Turn performance perception into a
positive connotation
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26. Perception of Germany in the US shows need for action.
Step 3: Evaluation and Comparison
> Perception of Germany in US media is relatively
negative and often reflects anger.
> Performance orientation is strong, seen as
positive in the context of a strong economy.
> However, Germany is viewed as a powerhouse,
not necessarily in a positive way.
> Perceptions expressed on Twitter reflect those
in general media.
> Perceptions more negative in conservative
states (e.g. Texas) vs. liberal (e.g. New York).
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27. Challenges
Step 4: Recommendations
> Perception beats performance – What people
believe or feel about a brand carries more weight
than its long-term performance.
> Opinion beats factual reasoning – People are
looking for confirmation of their deeply held
views, tied to their social and cultural identity.
The answer: an advanced communication
strategy to counteract these challenges and
strengthen the perception of Germany in the US.
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28. Where do we go from here?
> Working assumption: Germany has lost relevance in the United
States;
> Question: What can Germany do, and how transatlantic institutions
help, to improve perceptions of Germany in the US?
> Mismatch between Big Data Analytics and Stakeholder Survey;
> Strong on “Performance”, but that is not always good;
> Weak on “Sympathy” and “Character”;
> Need to re-think communication strategy for Germany;
> Along the lines of “Performance Plus”.
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