17 1, 2014 4, pp.3~34

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K-pop 15

(%)

(%)

(Ballad) 124 32.0%

1

1 11 2.8%

(R&B) 49 12.7% 1 ~ 1 10 44 11.4%

(Dance) 45 11.6% 1 11 ~ 1 20 76 19.6%

(Electronic) 91 23.5% 1 21 ~ 1 30 86 22.2%

/(Hip-Hop/Rap) 40 10.3% 1 31 ~ 1 40 77 19.9%

(Rock) 19 4.9% 1 41 ~ 1 50 51 13.2%

(Folk) 10 2.6% 1 51 ~ 2 20 5.2%

(Etc.) 9 2.3% 2 22 5.7%

Noisy:Lo-Fi

Noisy(Lo-Fi) 183 47.3%

3 8 2.1%

Noisy(Lo-Fi) 204 52.7% 3 ~ 3 20 65 16.8%

207 53.5% 3 21 ~ 3 40 117 30.2%

180 46.5% 3 41 ~ 3 59 109 28.2%

95, 105 .

-(Lo-Fi)

. BPM .

28 ,

6 . A C

. A Verse , C

(Chorus) . ABCD, ABC,

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b-part, C Chorus, D Bridge .

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16

(%)

(%)

ABCD 134 34.6%

4 ~ 4 20 45 11.6%ABC 70 18.1% 4 21 ~ 4 40 31 8.0%ACD 66 17.1% 4 41 ~ 4 59 8 2.1%AC 27 7.0% 5 4 1.0%

CABCD 74 19.1%

298 77.0%CACD 16 4.1% 28 7.2%%

/

= Hook 363 93.8% 2 0.5%

Hook 24 6.2% 11 2.8%

246 63.6% 40 10.3%/ / 95 24.5% 6 1.6%

46 11.9% 1 0.3%

189 48.8% 1 0.3%

198 51.2%

139 35.9%

180 46.5% 131 33.9%

207 53.5% 116 30.0%

5 74 19.1% 1 0.3%

265 68.5%

6 ~ 10 48 12.4% 122 31.5%

11 ~ 15 104 26.9%

315 81.4%16 ~ 20 79 20.4%

71 18.3%21 ~ 25 57 14.7%

1 0.3%26 ~ 30 13 3.4%

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31 12 3.1% () 99.18

.

1.

. (factor analysis) .

K-pop 17

0.5

. , ,

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. KMO .623, .000 .

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1 2 3 4

0.750 -0.028 -0.023 -0.226 0.683 0.085 0.008 0.022 0.666 -0.178 -0.158 0.123 0.559 -0.171 0.144 -0.007

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1 41.683 6 0.349 375 119.410 .000 2 35.260 6 0.452 375 78.039 .000 3 38.780 6 0.396 375 98.049 .000 4 55.018 6 0.136 375 405.424 .000

2.

7 .

.

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Bb(b) (Key of Eb) , / /

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K-pop 19

1 ()10)

.

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(Key of C) . ,

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() F() (Key of Eb)

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Am-F-C-G , Roly-Poly .

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Chorus 31% , 55%

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11)

K-pop 21

5 70% / .

17% 7%p . 2

.

3 , Hi-Fi

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15%p . ABC 41% 18%

23%p . 76%, 86%

, 1, .

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.

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Love Song .

5 80%

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60% . 5

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1 31~1 50 67%, 3 41 83%

K-pop 23

.

32% , 3

. 6 Hello Grand Final .

7 , 80% Hi-Fi

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. 160 100

93 10p .

AC , 1, .

, , AC AAC A(Verse)

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1 &

68% 14%p , 94%

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2

&

82%, Chorus 31% 55% 5 50% , 68%, 73%

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3

70% , ABC 41% , ( 76%, 86%) : , 17%, 26%

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4

, 50% AC(Verse, Chorus) 31% / / /,

, Love Song

5

, Noisy ()

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// + Noisy /

Hello, Grand Final

7 AC , AC

24

3.

(1)

. , (, ) ), ,

(, ), OST, , , .

. 5, 4

. , .

2010~2011 Top200 , 59%,

48% ( 4%, 8%),

19% . 8%,

3%, 10%, 8%.

17%, 22%, 18%, 24%, 20%, 57%, 19%, 13%, 11% .

(%)

227 59% 160 41%

186 48% 201 52%

16 4% 32 8%

74 19% 31 8% 10 3%

(OST) 40 10% 33 8%

13)

1 65 17%2 85 22%3 68 18%4 93 24%5 76 20%

14)

1 219 57%2 74 19%3 51 13%4 43 11%

13) 1 YG, 2 , CJ E&M, 3 SM, , , , 4 JYP,, , ,

K-pop 25

(2)

. , 1 2 ,

. 2 4 37% .

3 64% , 14%

. 29%, 31%

. 4 . ,

13%, 19%, 16% 10%p,

11%p, 8%p . 5 85%, 83%

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. 6 .

20%p , 3%p

. ,

. 7 67%

.

1 & , (18%) 3, 4, 5 63%

2

&

, (16%) (21%),4 (37%)

3 (31%) (64%), (14%) (29%), (26%)

4 (13%) (22%)

5 (85%) (83%) ( 1 2 80%)

6 & (31%) ( 24% )

7 AC

(67%) (67%) (56%)

DSP, F&C Music 14) 1 , CJ E&M, 2 KMP , KT, Universal Music,

3 SM, Sony Music,

26

(3)

, .

5%, 1% .

.

, 7 3 .

, 5 4 . , AC

,

.

N 1 2 3 F-test(p-value)

3 37 1,586,366

2.668 (.015*)

6 65 1,609,807 1,609,8072 68 1,674,620 1,674,6204 29 1,845,957 1,845,957 1,845,9571 55 1,860,534 1,860,534 1,860,5345 82 1,894,901 1,894,9017 8 1,969,386

.126 .111 .485

N 1 2 F test(p-value)

3 35 10,958,078

3.22 (0.004**)

1 59 12,903,251 12,903,251

7 6 13,833,372 13,833,372

2 63 14,028,011 14,028,011

6 60 14,321,066 14,321,066

4 27 15,233,989

5 82 15,489,448

.069 .176

K-pop 27

.

K-pop

.

. ,

.

. (Dan Levitin)

DNA 500 .

( 2009).

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(University of Bristol 2012).

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K-pop 29

.

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30

.

(2001). , .

(2001). , .

, (2005). , , 16(2): 1-14.(1999). :

, . (2009). , .(2001). MP3 -

, (2003). ,

.

(2009) : , .(1998).

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, , 13(4): 102-119(2007). ,

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(1999). , ., (2011). , . (2005). , , . (2007).

, .

K-pop 31

.

Apel, W. (1944). Harvard Dictionary of Music, Cambridge: Harvard University Press.

Asai, S. (2011). Demand Analysis of hit Music in Japan, Journal of Cultural Economics.

35: 101-117.

Bhattacharjee, S., Gopal, R. D., Lertwachara, K., Marsden, J. R., & Telang, R. (2007). The

Effect of Digital Sharing Technologies on Music Markets: A Survival Analysis of

Albums on Ranking Charts, Management Science, 53(9): 13591374.Burke, A. E. (1994). The Demand for Vinyl L.P. s 19751988, Journal of Cultural Economics,

18(1): 4164.Chung, K. H., & Cox, R. A. K. (1994). A Stochastic Model of Superstardom: An Application

of the Yule Distribution, Review of Economics and Statistics, 76(4): 771775.Cooper, G., & Meyer, L. B. (1960). The Rhythmic Structure of Music, Chicago : The University

of Chicago Press.

Creston, P. (1964). Principles of rhythm, New York: Franco Columbo.

Duke, R. A. (1987). Musicians Perception of Beat in Monotonic Stimuli, Unpublished

research paper, MENC Southern Division Conference, Orlando, FL, May.

Farnsworth P, R. (1969). The Social Psychology of Music(2nd ed.). Ames: Iowa State University

Press.

Fraisse, P. (1982). Rhythm and Tempo(Ed.), The Psychology of Music(pp. 149-180).

New York : Academic Press.

Gaston, E. T. (1968). Man and Music. In E. T. Gaston (Ed.), Music in Therapy (pp.7-21).

New York: Macmillan

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Crchestral Music among Musicians, Journal of Research in Music Education, 32:

195-204.

Geringer, J. M., Madsen, C. K., & Duke, R. A. (1993). Perception of Beat Note Change

in Modulating Tempos, Council for Research in Music Education, 119: 49-57.

Gordon, E. (1971). The Psychology of Music Teaching. Englewood Cliffs, NJ : Prentice-Hall.

Hamlen, W. A. (1991). Superstardom in Popular Music: Empirical evidence, Review of

Economics and Statistics, 73(4): 729733.Lundin, R, W. (1967). An Objective Psychology of Music(2nd ed.), New York: Ronald Press

MacDonald, M. (1988). The Economics of Rising Stars, American Economic Review,

32

78: 155-166

Mursell, J. L. (1937). Psychology of Music, New York: McGraw-Hill.

Mussulman, J. A. (1974). The Uses of Music : An Introduction to Music in

Contemporary American Life, Englewood Cliffs, NJ : Prentice-Hall.

Roederer, J. G. (1995). The Physics and Psychophysics of Music : An Introduction(3rd

ed.), New York : Spring-Verlag.

Rosen, S. (1981). The Economics of Superstars. American Economic Review, 71(5): 845858.Sink, P. E. (1984). Effects of Rhythmic and Melodic Alterations and Selected Musical

Experiences on Rhythmic Processing, Journal of Research in Music Education,

32, 177-194.

Sloboda, J. A. (1985). The Musical Mind, Oxford: Clarendon Press.

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of Research in Music Education, 31: 49-55.

K-pop 33

[Abstract]

Clustering K-Pop Hit Songs

Choi, Hyeok-Jae*Ahn, Sung-Ah**

The popularity of K-Pop has spread beyond Asia and into the global market.

However, although studies have focused on external factors of Korean music, such as

singers and media, there is a lack of research on the hit songs themselves.

The purpose of this study is to identify the characteristics of hit song types based on

musical factors in order to find the determinants of success in K-pop songs. Other external

characteristics such as sales are also considered to explain the differences among the types.

In this paper, data from the top 200 songs in a K-pop chart were collected and

cluster analysis was applied. The results show that there are seven hit song groups that

reflect the recent trends in the music market. First, recent hit songs have more complex

forms than older hit songs. Even songs with simple forms can have appeal to mass consumers

by using different compositions and arrangements. Second, dance music, including electronica,

has had a significant impact on K-pop, which shows an active embracing of trendy pop

arrangements and sounds. The current popular music of South Korea seems to be as

competitive as its overseas counterparts in the global market. Third, rock and indie music

with low market shares in the environment of K-pop has grown considerably through television

programs. Last, collaborations such as works that involve feature singers promote exchanges

and development between different genres.

This study plays the role of a bridge between the knowledge of music and economic

methodologies. Furthermore, the results based on musical factors have helped identify

recent music trends and offer hit musical notes and characters, topics that have not been

discussed in previous studies. Such data may be useful for producers and creators in

* Chugye university for the Arts, Graduate school of Culture and Ats Business, Department of Entertainment Business, Master of Business Administration, swedien@nate.com

** Chugye university for the Arts, Department of Film and Entertainment. Professor, jolean@chugye.ac.kr.

34

composing popular songs and developing marketing strategies.

Key Words : K-pop, music, music industry, hit song, cluster analysis