Exceptional Collaboration Patterns in Music Genre Networks

Gabriel P. Oliveira, Mirella M. Moro
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引用次数: 2

Abstract

Music is one of the world’s most important cultural forms, and also one of the most dynamic. Such a dynamic nature can directly influence artists’ careers and reflect their success. In this work, we combine social networks and data mining techniques to analyze musical success from a genre-oriented perspective. Our goal is to mine exceptional collaboration patterns in success-based genre networks where the success deviates from the average. We conduct our analyses for global and eight regional markets, and the results show that each market has specific patterns of genre connections in which success is above average. Hence, our findings serve as a first step in developing strategies to promote future song releases across the world.
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音乐类型网络中的特殊合作模式
音乐是世界上最重要的文化形式之一,也是最具活力的文化形式之一。这种动态性可以直接影响艺术家的职业生涯,反映他们的成功。在这项工作中,我们结合了社交网络和数据挖掘技术,从面向类型的角度分析音乐的成功。我们的目标是在基于成功的类型网络中挖掘特殊的合作模式。我们对全球市场和8个地区市场进行了分析,结果显示,每个市场都有特定的类型联系模式,其成功程度高于平均水平。因此,我们的研究结果可以作为制定策略的第一步,以促进未来歌曲在全球的发行。
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