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http://dx.doi.org/10.7465/jkdi.2015.26.3.619

Performance analysis of volleyball games using the social network and text mining techniques  

Kang, Byounguk (EnSOFTechnology Inc.)
Huh, Mankyu (Department of Molecular Biology, Dongeui University)
Choi, Seungbae (Department of Data Information Science, Dongeui University)
Publication Information
Journal of the Korean Data and Information Science Society / v.26, no.3, 2015 , pp. 619-630 More about this Journal
Abstract
The purpose of this study is to provide basic information to develop a game strategy plan of a team in a future by identifying the patterns of attack and pass of national men's professional volleyball teams and extracting core key words related with volleyball game performance to evaluate game performance using 'social network analysis' and 'text mining'. As for the analysis result of 'social network analysis' with the whole data, group '0' (6 players) and group '1' (11 players) were partitioned. A point of view the degree centrality and betweenness centrality in 'social network analysis' results, we can know that the group '1' more active game performance than the group '0'. The significant result for two group (win and loss) obtained by 'text mining' according to two groups ('0' and '1') obtained by 'social network analysis' showed significant difference (p-value: 0.001). As for clustering of each network, group '0' had the tendency to score points through set player D and E. In group '1', the player K had the tendency to fail if he attack through 'dig'; players C and D have a good performance through 'set' play.
Keywords
Centrality measurement; social network analysis; text clustering analysis; text mining technique; web science;
Citations & Related Records
Times Cited By KSCI : 9  (Citation Analysis)
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