Browse > Article
http://dx.doi.org/10.5392/JKCA.2016.16.09.127

The Relationship between Centrality and Winning Percentage in Competition Networks  

Seo, Il-Jung (광운대학교 경영대학 경영학부)
Baik, Euiyoung (광운대학교 대학원 경영정보학과)
Cho, Jaehee (광운대학교 경영대학 경영학부)
Publication Information
The Journal of the Korea Contents Association / v.16, no.9, 2016 , pp. 127-135 More about this Journal
Abstract
We identified a competition network which has never been studied before and investigated the relationship between centrality of participants in singing competition and their winning percentage within the competition network. We collected competition data from 'Immortal Songs: Singing the Legend', which is a Korean television music competition program, and constructed a competition network. We calculated centrality and winning percentage and analyzed their relationship using correlation analysis, regression analysis, and visualization. There are four main findings in this research. First, a competition network is a scale-free network whose degree distribution follows a power law. Second, there is a logarithmic relationship between the count of competition and closeness. Third, winning percentage converges to approximately 60% for players who have participated in more than 20 competitions. Lastly, a strength of opponents affects approximately 23% of winning percentage for players with less than 20 competitions. The academic significance of this study is that we pioneered the definition of the competition network and applied social network analysis method. Another significant contribution of this paper is that we found explicit patterns between the centrality and winning percentage, suggesting ways to improve social relationship in competition network and to increase winning percentage.
Keywords
Social Networks; Centrality; Competition; Winning Percentage;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
연도 인용수 순위
1 http://dic.naver.com
2 S. P. Borgatti, M. G. Everett, and J. C. Johnson, Analyzing Social Networks, London: SAGE Publications Limited, 2013.
3 M. K. Ahuja, D. F. Galletta, and K. M. Carley, "Individual centrality and performance in virtual R&D groups: an empirical study," Management Science, Vol.49, No.1, pp.21-39, 2003.   DOI
4 R. Cross and J. N. Cumming, "Tie and network correlations of individual performance in knowledge intensive work," Academy of Management Journal, Vol.47, No.6, pp.928-937, 2004.   DOI
5 R. T. Sparrowe, R. C. Linden, S. J. Wayne, and M. L. Kraimer, "Social networks and the performance of individuals and groups," Academy of Management Journal, Vol.44, No.2, pp.316-325, 2001.   DOI
6 문주영, "친구관계 네트워크가 학습성과에 미치는 영향 - S대학 비서학전공 전문대학생들을 중심으로," 한국콘텐츠학회논문지, 제15권, 제11호, pp.616-625, 2015.   DOI
7 옥경영, 홍재원, "청소년의 사회적 네트워크에서의 지위(social standing)가 온라인 사회적 활동(social activity)에 미치는 영향 연구," 한국콘텐츠학회논문지, 제12권, 제5호, pp.370-379, 2012.
8 M. G. Everett and S. P. Borgatti, "Extending centrality," Models and Methods in Social Netwokr Analysis, Vol.35, pp.57-76, 2005.
9 L. C. Freeman, "Centrality in social networks: conceptual clarification," Social Networks, Vol.1, No.3, pp.215-239, 1978.   DOI
10 P. Bonacich, "Factoring and weighting approaches to status cores and clique identification," Journal of Mathematical Sociology, Vol.2, No.1, pp.113-120, 1972.   DOI
11 P. Bonacich, "Some unique properties of eigenvector centrality," Social Networks, Vol.29, No.4, pp.555-564, 2007.   DOI
12 http://www.kbs.co.kr/2tv/enter/satfreedom/view/vod/index.html
13 A. L. Barabasi and R. Albert, "Emergence of scaling in random networks," Science, Vol.286, No.5439, pp.509-512, 1999.   DOI