1. *http://a.oops-music.com http://www.barks.jp/news/?id=
/doops/09.php 1000052436
EMPIRICAL STUDY
OF
SUPERSTAR PHENOMENON
Takeaki Tsutsumi
Media Environment Laboratory
The University of Tokyo

2. OVERVIEW
http://www.lastfm.jp/music/Bon+J
ovi/+images/136716
1. Introduction
2. Methods
3. Results*
4. Discussion
5. Conclusions
6. Future Research
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3. BACKGROUND
 significant feature of media contents industry：
⇒ concentrate sales in just small numbers of stars or films
＝
 “whereinrelatively small numbers of people
earn enormous amounts of money and
dominate the activities in which they engage”
Rosen (1981) 「The Economics of Superstars」
3
3

4. BACKGROUND
movie retail music market
Fig. 1 Variation of Gini Index (Japan)*
4
*Yamamoto et al.(2002)
「Information Channel Effect in Music CD Market : An Agent-based Approach to Winner-Take-

5. BACKGROUND
Theoretical study Empirical study
① Rosen (1981)
Type 1
Quality
industry statistics
② Adler (1985)
Recognition Type 2
Verification of effects on
③ McDonald (1988) success at moneymaking in
Multiple markets contents industry
Fig. 2 Research type 5
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6. BACKGROUND
Table 1 Detailed outline of major research*
Analysis
Author Data Research object Year
Results
Rosen - Quality Theoretical study 1981
(Modelization)
Popular music Recognition
Adler Empirical study 1985
(America) degree
Popular music Multiple
McDonald Empirical study 1988
(England) market
*Deguchi, Hiroshi. Tanaka, Hideyuki and Koyama, Yusuke.
Contentsu Sangyou Ron. Tokyo Daigaku Syupan Kai, 2009
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7. BACKGROUND
Table 2 Country and distribution of superstar research
Country / Area (Top 15) Number of papers （2066） Rate (%)
USA 1230 38.53
ENGLAND 285 8.93
CANADA 131 4.10
AUSTRALIA 87 2.73
FRANCE 61 1.91
GERMANY 48 1.50
CHINA 29 0.91
NETHERLANDS 27 0.80
SCOTLAND 26 0.82
ITALY 24 0.75
SOUTH KOREA 22 0.69
ISRAEL 21 0.66
SWITZERLAND 21 0.66
TAIWAN 20 0.63
SPAIN 19 0.60 7
BELGIUM 15 0.47
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Source: Web of Science

8. PROBLEMS
Ambiguity definition of superstar in previous studies
Complexity contributing factor of superstar phenomenon
・necessity of systematic approach (Academic Landscape Map)
Necessity empirical study in Japan
・Make a difference of biased areal distribution in previous studies
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9. HYPOTHESIS
Identify operational definition of Superstar
・investigation of definition from previous studies
Extract contributing factor of superstar phenomenon
・perform computational citation network analysis to
provide academic landscape map
・perform statistical analysis of raw data from Japanese film industry
Examine impact of Internet
・investigate search volume index about targets using
Google Trend and YouTube
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9

10. METHODS 1
Movie industry Investigation of attendance rate and
→ famous actor market share
→ famous movie (avoid influence of population difference)
(research object)
→ film attendance rate and film market share
(raw data from Japanese film industry)
Quality: Recognition degree:
・based on evaluation of film critics ・based on movie advertising on television
⇒Extract film score from Kinema Junpo ⇒Investigation of investment from television
(journal of filmmakers) company to film making
(statistical data)
・Kinejyun Souken Hakusyo 『Movie Business Data book 2008』 10
・Motion Picture Producers Association of Japan 『Movie Industry Statistics in Japan』 (1986～2006)

11. METHODS 2
Extract papers from database
Network analysis inter-papers
paper
citation Clustering
(Newman, 2004) Visualization
Fig. 3 Analysis Steps in Citation Network Analysis* 11
*Sakata et al. : ”Systematic Identification of Academic Knowledge in
Patent & Innovation” ICMSIE2010,(December,2010)

12. METHODS 3
 Music
YouTube
・Correlations between Top 10 US musician’s YouTube plays
and incomes in U.S.
 Movies
Google Trend
・Correlations between hit film’s search volume index and
film box-office takings in Japan
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13. RESULTS 1
Table 3. Market share and number of hit films in Japan (2007)
Operational Definition of
Superstar film in Japan :
『More than five billion yen
at the box office』
13
Fig.4 Relationships between Market share or attendance
share and film box-office takings (average market)

14. RESULTS 2-1
Source: Web of Science
Cluster of superstar
phenomenon
(555 papers)
cluster count 71
node count 2766
edge_count 7858
facet_count 4830
average year 2006.3
(feature amount of
maximum connected 14
1 component)
4 Fig. 5 Academic Landscape Map

15. RESULTS 2-2
Fig. 6 Top100 keyword analysis (2nd cluster) 15
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16. RESULTS 2-3
Over 5 billion yen Under 5 billion yen
300 450
Significan 400 Not
250
Significant
Kinema Junpo Score
Kinema Junpo Score
350
t
300
200 correlatio
250
n
150
200
150
100 y = 0.655x - 9.039 y = -0.440x + 59.06
R² = 0.469 100 R² = 0.002
50 50
0
0
0 10 20 30 40 50 60
0 50 100 150 200 250 300 350
The film box-office takings The film box-office takings
(million yen) (million yen)
Fig. 7 Comparing correlations between Kinema Junpo 16
1 Score and film box-office takings in Japan
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17. RESULTS 2-4
Fig. 8 Relationships between recognition and film box-office
takings (average) 17
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19. DISCUSSION
Redefinition of hypothesis
one-way media (television, etc.) cause superstar phenomenon
Assessment of cause-and-effect logic
cause-and-effect between recognition degree or quality and
the phenomenon
Validity of data
necessity to verify credibility of YouTube plays
Another definition of superstar
necessity to identify another definition of superstar 19
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20. CONCLUSIONS
1st empirical study of superstar
phenomenon in Japan
1. Identify operational definition of Superstar film
→ More than five billion yen at box office
2. Extract contributing factor of superstar phenomenon
→ Recognition degree and quality are essential pieces
of superstar phenomenon
3. Examine impact of Internet
→ Internet has indirect effect on the phenomenon
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21. FUTURE RESEARCH
 Improve Rosen model based on the behavioral economics
 Analyze another industry or field
 Simulation model building of superstar phenomenon
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22. Thank you for your
kind attention!
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