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引用次数: 0
摘要
为什么有些歌曲和音乐人获得了成功,而有些却没有?我们的研究表明,原因之一可能是 "先行者优势":站在新音乐流派基础上的艺术家往往比后来加入这些流派的艺术家更成功。为了验证这一假设,我们分析了一个包含超过 92 万首歌曲的庞大数据集,其中包括 110 种音乐类型:10 种是有意选择并预先登记的,100 种是随机选择的。为此,我们从两个音乐服务机构收集了数据:Spotify 提供歌曲成功率的详细信息(每首歌曲被收听的精确次数),而 Every Noise at Once 则为音乐人提供详细的流派标签。在 110 个流派中,有 91 个流派显示出了先行者优势,这清楚地表明先行者优势是音乐成功和进化的重要机制。
Why do some songs and musicians become successful while others do not? We show that one of the reasons may be the “first-mover advantage”: artists that stand at the foundation of new music genres tend to be more successful than those who join these genres later on. To test this hypothesis, we have analyzed a massive dataset of over 920,000 songs, including 110 music genres: 10 chosen intentionally and preregistered, and 100 chosen randomly. For this, we collected the data from two music services: Spotify, which provides detailed information about songs’ success (the precise number of times each song was listened to), and Every Noise at Once, which provides detailed genre tags for musicians. 91 genres, out of 110, show the first-mover advantage—clearly suggesting that it is an important mechanism in music success and evolution.
期刊介绍:
EPJ Data Science covers a broad range of research areas and applications and particularly encourages contributions from techno-socio-economic systems, where it comprises those research lines that now regard the digital “tracks” of human beings as first-order objects for scientific investigation. Topics include, but are not limited to, human behavior, social interaction (including animal societies), economic and financial systems, management and business networks, socio-technical infrastructure, health and environmental systems, the science of science, as well as general risk and crisis scenario forecasting up to and including policy advice.