K-Pop Idol Industryxs3d.kaist.ac.kr/Lab Activity/2014 summer lab seminar/Idol Industry... ·...

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K-Pop Idol Industry 20100663 Minhyung Lee

Transcript of K-Pop Idol Industryxs3d.kaist.ac.kr/Lab Activity/2014 summer lab seminar/Idol Industry... ·...

K-Pop Idol Industry 20100663 Minhyung Lee

1. K-Pop Idol History 2. Idol Industry Factor

3. Regression Analysis

4. Result & Interpretation

K-Pop Idol History (1990s)§ Turning�point�of��Korean�Music�

history�: Incorporation�of�American�popular�music�styles. Firstly�introduced�by�Seotaji�&�Boys(1992)

§ Starting�of�the�Idol�Training�system�by�Lee,�Su-man,�the�founder�and�producer�of�the�SM�Entertainment.�-�1st�generation�of�Idol�stars�came�out�:�H.O.T.(1996)

§ S.E.S.(1997),�Sechs�Kies(1997),�FIN.K.L(1998),�Shinhwa(1999),�god(1999)

K-Pop Idol History(2000s)§ Early�2000s�:�Starting�of�Korean�

flow�upon�Japan�&�Adaption�of�systematic�idol�training�syste�-�BoA(2000)

§ Mid�of�2000s�:�New�revival�and�rising�of�idol�industry�- DBSK(2003),�SS501(2005),�Super�Junior(2005),��BIG�BANG(2006)

§ End�of�2000s�:�Opening�of�the�Idol�Golden�Age�&�Change�in�the�concept�of�Idol�=�Total�Entertainer�&�Expansion�of�Korean�Wave�-�Wonder�Girls(2007),�Girls'�Generation(2007),�SHINee(2008),�2NE1(2009),�f(x)(2009),�4minute(2009)�

K-pop Idols' Golden Age - 2010s

§ More�than�two�hundreds�of�idol�groups

§ Expansion�of�K-Pop�to�foreign�countries.

§ Korean�Wave�&�Globally�big�Fan�culture

§ Considered�as�one�step�to�be�a�star

§ Foreign�Market�is�the�main�part�of�their�profit

§ �.....K-Pop�Industry�Statistics

Year Total�Exports�in�US�$ Youtube�Views

2008 $16.5�million

2009 $31.3�million

2010 $84.9�million 800�million

2011 $180�million 2.2�billion

2012 $235�million 7.0�billion

Exports�by�Contry�in�US�Dollar

Year Japan China

2008 $11.2�million $1.80�million

2009 $21.6�million $2.36�million

2012 $204�million $3.60�million

Ø Golden�Age�of�Idol�Industry�

Idol�industry�becomes�main�profit�of�music�industry��

Costs for 5-member Idol GroupMontly�Fixed�Cost Cost�for�Releasing�New�Album

Rent�of�Dorm $1,000 Composition�Cost $12,000

Dance�Room $1,000 Recording�Master $8,000

Food�&�Snack $3,000 Photography $3,000

Dance�Lesson $2,000 Album�Jacket�Design $4,000

Vocal�Lesson $3,000 Costume�Design $20,000

Acting�Lesson $2,000 Music�Video�Recording $50,000

Beauty�&�Cosmetics,�Plastic�Surgery

$10,000 Promotion $100,000

Director�Casting $3,000 Hair�&�Make-up $5,000

Staff�wage $15,000 Dance�Creation $6,000

Back�Dancer�Wage $7,000

Sum $40,000 Etc $215,000

v More�than�$400,000�to�train�groups�and�release�one�album�in�6�months��

K-pop Idols' Golden Age - 2010s

§ But�also�Red�Ocean�of�Idol�Industry

§ Too�many�idol�groups�these�days�-�More�than�200�groups�in�total

§ Lots�of�money�spent�to�make�a�debute�of�one�idol�group�

Year Number of Groups Debuted

2010 19

2011 30

2012 37

2013 14

v �From�now�on,�they�need�to�access�to�this�industry�systematically,�which�properties�and�factors�are�needed.�

1. K-Pop Idol History

2. Idol Industry Factor3. Regression Analysis

4. Result & Interpretation

K-pop Idols' Revenue

1.Streaming�Music�File��(MP3�File)

2. �Album�Sales

3.Concert�/�Musical�Performances

4.MV�Advertisements

5. Individual�Acts�(ex.�Drama�/�Movie�/�Musical)

6. International�Events

Factors related to Idol Industry

�Outer�result�of�Idol�groups

§ �Sales�amount�of�Music�albums

§ �Online�Download�Sales

§ �Number�of�View�of�Music�Videos�on�Youtube

§ Pretty,�Handsome�face�&�Skinny�body�-�TV,�Movie,�CF

§ Good�Singing�Skills�-�Basic�skill�for�singer,�Musical�Act

§ Gorgeous�Dancing�Skills�-�Basic�skill�for�k-pop�star�-�Basic�skill�for�k-pop�star

§ Number�of�Members

Ø Internal factor of Each Idol Groups

Data Collection§ Music�sales�amount�&�online�

download�from�Gaon�Chart,�

Korean�Bill-board

§ Number�of�Views�from�

Youtube

§ Dance�Level�from�WAWA�

Dance�academy

§ Information�about�each�

groups�from�Naver

§ Appearance�and�Popularity�

from�Survey

Data Collection Album Sales & Online Download Sales

§ Album�Sales�Amount�from�Album�Chart�of�Gaon�Chart

§ Music�Files�Salen�Amount�from�Download�Chart�in�Gaon�Chart

§ Some�Music�Files�didn't�have�the�data�on�the�Top�100�Download�Chart,�even�though�that�albums�were�on�the�Top�100�Album�Chart

§ I�divided�the�download�sales�amount�by�100,000,�so�that�the�scores�of�download�amount�of�all�groups�can�be�put�between�0�and�5.

Sales�Data

Data Collection Youtube Views & Dance Level

§ Dance�Level�dat�from�the�wawa�dance�academy,�which�is�one�of�the�famous�dance�group�in�Korea

§ They�divided�the�level�from�1�to�7.�1�is�the�easiest�and�7�is�the�hardest.

§�Got�the�youtube�music�video�views�from�the�number�shown�on�the�bottom�of�videos.�§�Divided�the�number�of�views�according�to�the�year�when�the�song�came�out,�so�that�I can�get�the�yearly�view.

Dance�Level

Youtube�Views

Data Collection Appearance & Popularity

§�For�Popularity�data,�I�got�the�data�of�each�group�from�the�survey.§�Popularity�score�is�from�1�to�10.�10�is�the�most�popular�group.§�For�equality,�I�divided�the�score�according�to�each�groups'�debute�year,�because�usually�the�old�groups�have�more�popularity.

§ For�appearance�data,�I�got�the�data�of�each�members�in�one�group�and�divided�the�sum�of�the�scores�by�the�number�of�members,�so�that�I could�get�the�average�appearance�data.

§ Apperance�score�is�from�1�to�5.�5�is�the�most�gorgeous�looking

Appearance

Popularity

Data

1. K-Pop Idol History

2. Idol Industry Factor

3. Regression Analysis4. Result & Interpretation

Regression Model 1(Album Sales Amount)

§ y�=�-642157.5�+�37588x1�+�6173.9x2�+�490.1x3�+�10560x4+49186.4x5

£ y�:�Album�Sales�Amount

£ x1�:�Popularity

£ x2�:�Vocal�Level

£ x3�:�Dance�Level

£ x4�:�Appearance

£ x5�:�Number�of�

Members

Estimate Std. Error t-value Pr(>|t|)

(Intercept) -642157.5 180489.7 -3.558 0.00146

Popularity 37588 21261.2 1.768 0.08881

Vocal 6173.9 2017.3 3.06 0.00508

Dance 490.1 9926.1 0.049 0.961

Appearance 10560 36871.8 0.286 0.77684

Members 49186.4 10645.4 4.62 0.0000915

Regression Model 1

§ Residual�standard�error:�68990�on�26�degrees�of�freedom

§ Multiple�R-squared:��0.6373

§ Adjusted�R-squared:��0.5676�

§ F-statistic:�9.137�on�5�and�26�DF

§ p-value:�0.00004108 ���

→��Since�p-value�is�very�low,��this�model�is�significant

§ y�=�-642157.5�+�37588x1�+�6173.9x2�+�490.1x3�+�10560x4+49186.4x5

Regression Analysis 1

§ In�the�Residual�-�Estimate�graph,�it�showed�some�pattern.�Therefore�this�model�is�not�covariant.

§ In�the�Normality�graph,�it�follwed�the�normality�pattern.

§ Residual�-�Estimate�Graph § Normality�Graph

Hypothesis Test for Subset 1 Ø�Hypothesis�for�Subset�Model§ H0�:�β3�=�β4��=�0�

§ H1�:�not�H0

X3�:�DanceX4�:�Appearance

Estimate Std.�Error t-value Pr(>|t|)

(Intercept) -613522 145042 -4.23 0.000226

Popularity 36930 19369 1.907 0.066877

Vocal 6232 1937 3.216 0.003266

Members 50089 9544 5.248 1.41E-05

§�Residual�standard�error:�66580�on�28�degrees�of�freedom�§�Multiple�R-squared:��0.6362, Adjusted�R-squared:��0.5972�§�F-statistic:�16.32�on�3�and�28�DF,��p-value:�2.509e-06

§ Reduced�Model

§ y�=�-613522�+�36930x1�+�6232x2�+�50089x5

Hypothesis Test Result 1

Ø Result§ y�=�-613522�+�36930x1�+�6232x2�+�50089x5

§F�=�{(124140000000�­�123746958742)�/�2}�/�

(123746958742/26)�=�0.04129

§0.04129�<�F�0.95(2, 26)�=��3.37,�so�H0 is�not�rejected�

§As�a�result, Reduced�Model�is�more�adequate.

Ø�Hypothesis�for�Subset�Model§ H0�:�β3�=�β4��=�0�

§ H1�:�not�H0

X3�:�DanceX4�:�Appearance

Regression Model 2 (Online Download Sales)

§ y�=�-0.99212�-�0.27406x1�+�0.07736x2�-�0.17606x3�-�0.6473x4�+�0.19617x5

£ y�:�Online�Download�Sales

£ x1�:�Popularity

£ x2�:�Vocal�Level

£ x3�:�Dance�Level

£ x4�:�Appearance

£ x5�:�Number�of�

�����������Members

Estimate Std.�Error t-value Pr(>|t|)

(Intercept) -0.99212 3.51666 -0.282 0.7801

Popularity -0.27406 0.41425 -0.662 0.5141

Vocal 0.07736 0.03931 1.968 0.0598

Dance -0.17606 0.1934 -0.91 0.371

Appearance -0.6473 0.71841 -0.901 0.3759

Members 0.19617 0.20741 0.946 0.353

Regression Model 2

§ Residual�standard�error:�1.344�on�26�degrees�of�freedom

§ Multiple�R-squared:��0.2158,

§ Adjusted�R-squared:��0.06505�

§ F-statistic:�1.431�on�5�and�26�DF,�

§ p-value:�0.2462

→��Since�p-value�is�low,��this�model�is�significant

�y�=�-0.99212�-�0.27406x1�+�0.07736x2�-�0.17606x3�-�0.6473x4�+�0.19617x5

Regression Analysis 2

§ In�the�Residual�-�Estimate�graph,�it�showed�some�pattern.�Therefore�this�model�is�not�covariant.

§ In�the�Normality�graph,�it�slightly�follwed�the�normality�pattern.

§ Normality�Graph§ Residual�-�Estimate�Graph

Hypothesis Test for Subset 2 Ø�Hypothesis�for�Subset�Model§ H0�:�β1�=�β3��=�β4�=�β5�=�0�

§ H1�:�not�H0

X1�:�PopularityX3�:�DanceX4�:�AppearanceX5�:�Number�of�Members

Estimate Std.�Error t-value Pr(>|t|)

(Intercept) -2.33337 1.58128 -1.476 0.1505

Vocal 0.0643 0.02799 2.297 0.0288

§�Residual�standard�error:�1.303�on�30�degrees�of�freedom�§�Multiple�R-squared:��0.1496, Adjusted�R-squared:��0.1213�§�F-statistic:�5.278�on�1�and�30�DF,��p-value:�0.02875→��Since�p-value�is�low,��this�model�is�significant

§ Reduced�Model

§ y�=�-2.33337�+�0.0643x2�

Hypothesis Test Result 2

Ø�Result�§ y�=�-2.33337�+�0.0643x2�

§�F�=�{(50.946�­�46.977)�/�4}�/�(46.977�/�26)�

������=�0.549173

§�0.549173�<�F�0.95(4, 26)�=��2.74,�so�H0 is�not�rejected�

§�As�a�result, Reduced�Model�is�more�adequate.

Ø�Hypothesis�for�Subset�Model§ H0�:�β1�=�β3��=�β4�=�β5�=�0�

§ H1�:�not�H0

X1�:�PopularityX3�:�DanceX4�:�AppearanceX5�:�Number�of�Members

Regression Model 3 (Youtube Video Views)

§ y�=�-9412046�+�1344092x1�+�370465x2�+�1436490x3�-�8468098x4�+�3061916x5

£ y�:�Youtube�Music�Video�Views

£ x1�:�Popularity

£ x2�:�Vocal�Level

£ x3�:�Dance�Level

£ x4�:�Appearance

£ x5�:�Number�of�

�����������Members

Estimate Std.�Error t-value Pr(>|t|)

(Intercept) -9412046 21670847 -0.434 0.6676

Popularity 1344092 2552772 0.527 0.603

Vocal 370465 242217 1.529 0.1382

Dance 1436490 1191800 1.205 0.2389

Appearance -8468098 4427090 -1.913 0.0668

Members 3061916 1278161 2.396 0.0241

Regression Model 3

§ Residual�standard�error:�8283000�on�26�degrees�of�freedom

§ Multiple�R-squared:��0.4114

§ Adjusted�R-squared:��0.2982�

§ F-statistic:�3.635�on�5�and�26�DF,��p-value:�0.0126

→��Since�p-value�is�low,��this�model�is�significant

�y�=�-9412046�+�1344092x1�+�370465x2�+�1436490x3�-�8468098x4�+�3061916x5

Regression Analysis 3

§ In�the�Residual�-�Estimate�graph,�it�showed�some�pattern.�Therefore�this�model�is�not�covariant.

§ In�the�Normality�graph,�it�follwed�the�normality�pattern.

§ Normality�Graph§ Residual�-�Estimate�Graph

Hypothesis Test for Subset 3 Ø�Hypothesis�for�Subset�Model§ H0�:�β1�=�β2��=�β3��=�0�

§ H1�:�not�H0

X1�:�PopularityX2�:�Vocal�LevelX3�:�Dance�Level

Estimate Std.�Error t-value Pr(>|t|)

(Intercept) 23146580 14218681 1.628 0.11436

Appearance -9347966 4460609 -2.096 0.04495

Members 2715356 854798 3.177 0.00352

§�Residual�standard�error:�8582000�on�29�degrees�of�freedom§�Multiple�R-squared:��0.2953, Adjusted�R-squared:��0.2467�§�F-statistic:�6.075�on�2�and�29�DF,��p-value:�0.006256→��Since�p-value�is�low,��this�model�is�significant

§ Reduced�Model

§ y�=�23146580�-�9347966x4�+�2715356x5�

Hypothesis Test Result 3

Ø Result�§ y�=�23146580�-�9347966x4�+�2715356x5�

§�F�=�{(2136000000000000�­�1783900000000000)�/�3}�/�������������������������������������������

(1783900000000000�/�26)�=�1.710597

§�1.710597�<�F�0.95(3, 26)�=��2.98,�so�H0 is�not�rejected�

§�As�a�result, Reduced�Model�is�more�adequate.

Ø�Hypothesis�for�Subset�Model§ H0�:�β1�=�β2��=�β3��=�0�

§ H1�:�not�H0

X1�:�PopularityX2�:�Vocal�LevelX3�:�Dance�Level

1. K-Pop Idol History

2. Idol Industry Factor

3. Regression Analysis

4. Result & Interpretation

Result Analysis§ Reduced�Model�1�(Album�Sales�Amount)§ y�=�-613522�+�36930x1�+�6232x2�+�50089x5§�Residual�standard�error:�66580�on�28�degrees�of�freedom�§�Multiple�R-squared:��0.6362, Adjusted�R-squared:��0.5972�§�p-value:�2.509e-06,�������������������������No�covariance�&�Normality

§ Reduced�Model�2�(Online�Download�Sales)§ y�=�-2.33337�+�0.0643x2§�Residual�standard�error:�1.303�on�30�degrees�of�freedom�§�Multiple�R-squared:��0.1496, Adjusted�R-squared:��0.1213�§�p-value:�0.02875����������������������������No�covariance�&�Weak�Normality

§ Reduced�Model�(Youtube�Music�Video�View)§ y�=�23146580�-�9347966x4�+�2715356x5�§�Residual�standard�error:�8582000�on�29�degrees�of�freedom§�Multiple�R-squared:��0.2953, Adjusted�R-squared:��0.2467�§�p-value:�0.006256����������������������������������������No�covariance�&�Normality

Most�Significant

Model�1�has�the�biggest�R-squared�and�the�smallest�p-valueTherefore,�Model�1�is�the�most�significant

Result Analysis§ Reduced�Model�1�(Album�Sales�Amount)

§ y�=�-613522�+�36930x1�+�6232x2�+�50089x5

Popularity VocalLevel

#�of�Members

§ More�popular�groups�have�more�amount�of�album�sales�because�of�the�

number�of�fans�will�be�more�than�non-popular�groups

§ If�the�vocal�level�is�high�in�the�group,�then�the�range�of�songs�can�be�wide.�

Therefore,�people�can�have�more�interest�to�their�songs.

§ If�the�number�of�members�are�many,�they�can�satisfy�different�tastes�of�

each�fans.�As�a�result,�more�people�will�buy�those�groups'�albums

Final Analysis and Limit§ For�the�idol�groups,�the�great�vocal�skill�can�be�

considered�as�the�most�important�factors.

§ Number�of�members�should�be�considered�too�when�the�agency�plans�to�make�a�new�idol�group.

§ Appearance�preference�is�very�different�from�person�by�person,�so�it�doesn't�have�to�be�considered�as�much�as�vocal�skills.

§ Dance�level�will�be�different�from�each�group's�songs,�so�the�dance�level�of�one�song�can't�be�representative�of�the�whole�groups'�dance�skill.

§ Also,�most�of�the�input�data�was�very�subjective,�which�means�those�can�be�different�if�I�get�it�from�different�people.�Because�of�this,�there�was�a�problem�of�lack�of�covariance.

References§ http://www.gaonchart.co.kr/chart/download.php?f_type=y

ear§ http://www.gaonchart.co.kr/chart/album.php?f_type=year§ http://lam01.tistory.com/277§ http://blog.naver.com/PostView.nhn?blogId=bluecheck9&l

ogNo=70124216973§ http://wawadance.com/§ http://www.youtube.com/channel/UCsEonk9fs_9jmtw9Pw

ER9yg

Thank You