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第18屆到第29屆臺灣金曲獎最佳國語男女歌手提名人創作角色分析

Creative Role Analysis of the Best Male/Female Mandarin Singer Nominees in Taiwan Golden Melody Awards (2007-2018)

摘要


本研究分析第18屆到第29屆最佳國語男女歌手獎提名人的創作角色,從歌手參與專輯單曲上創作類型切入,提名人除擔任歌曲演唱者外,是否會進一步參與作詞、作曲、編曲、製作等音樂創作工作,成為身分多元的創作歌手。且進一步描繪提名人與音樂工作者之間的網絡,以及歌手身分的多元性與其在音樂工作者社群中的位置之間的關係。歸結研究目的為:一、以社會網絡分析法描繪臺灣最佳男女歌手入圍專輯音樂工作者社群樣貌;二、呈現金曲獎最佳男女歌手提名人之身分多元程度與其參與音樂創作工作之類型;三、探討金曲獎最佳男女歌手提名人之身分多元程度與網絡地位之相關性。整體來說金曲獎最佳國語歌手音樂工作者社群網絡具有相當規模,且社群成員連結程度高,但是有別於小世界網絡現象,整體網絡平均群聚係數數值相對較低,顯示音樂工作者彼此之間合作對象多元,且並未偏好與特定音樂創作人合作之情形。另以每位音樂工作者合作程度進行分群,顯示整體網絡有明顯分群,且各分群社群網絡凝聚程度較高。本研究統計結果顯示歌手參與音樂創作工作主要是以作詞為主,作曲類型與監製類型次之,編曲類型最少。另外,本研究發現歌手身分多元程度越高,越能居於整體社群網絡的中心性位置,換言之,身分多元的創作歌手在進行音樂創作時,可以更容易觸及其他音樂工作者,並且較會尋求其他音樂工作者共同創作音樂作品。

並列摘要


A study was conducted to analyze the collaboration network of popular music production in Taiwan, using artists who took part in the works by the Best Male/ Female Mandarin Singer Award nominees of 18th to 29th Golden Melody as the study population. Overall, the best Mandarin singer music worker community network is quite large (diameter = 7), and the community members are highly connected (average path length = 2.156). However, unlike the small world network model, the whole the network average clustering coefficient value is relatively low (average clustering coefficient = 0.02), showing that the artists have a wide range of collaborators. In addition, a high modularity was observed (# of modules = 22, modularity score = 0.72), suggesting collaboration tend to be more cohesive around certain music styles. We also examined the relationship between an artists' network position and the diversity of the roles she/he played in the creative process such as lyricists, composers, producers, or arrangers. The diversity of an artist's creative role was calculated by Herfindahl-Hirschman Index. A significant correlation was found between a nominee's role diversity and his/her centrality.

參考文獻


Berardo, R.(2011).Networking networkers: An initial exploration of the patterns of collaboration among the members of a new community in political science.PS: Political Science & Politics.44,69-75.
Blondel, V. D.,Guillaume, J.-L.,Lambiotte, R.,Lefebvre, E.(2008).Fast unfolding of communities in large networks.Journal of Statistical Mechanics: Theory and Experiment.2008(10),1-12.
Borgatti, S. P.,Everett, M. G.,Johnson, J. C.(2013).Analyzing social networks.London, UK:Sage.
Hu, Y.,Zhang, J.,Bai, X.,Yu, S.,Yang, Z.(2016).Influence analysis of Github repositories.SpringerPlus.5
Potter, G. E.,Handcock, M. S.,Longini, I. M.,Halloran, M. E.(2012).Estimating within-school contact networks to understand influenza transmission.The Annals of Applied Statistics.6,1-26.

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