论文标题：Quantifying and predicting success in show business

期刊：Nature Communications

作者：Oliver E. Williams, Lucas Lacasa, Vito Latora

发表时间：2019/06/04

数字识别码： 10.1038/s41467-019-10213-0

原文链接： http://t.cn/AiNSjrtM

微信链接：https://mp.weixin.qq.com/s/xHcYDlJ2s7HXiUxedNVpAw

《自然-通讯》发表的一篇论文Quantifying and predicting success in show business 报告了一种机器学习方法，它可以预测一名电视或电影演员最高产的年份是否已经出现。这项研究认为最高产的年份倾向于出现在演员的事业发展初期，而且这种效应在女演员群体中更加明显，女演员的演艺生涯也有更大概率比男演员短。

图1 演员职业生涯的活跃模式。图源：Williams等

考虑到电影电视行业的失业率达90%，而且仅有约2%的荧幕演员能够通过表演维持生计，因此只要拥有充足的工作量（持续的产出），对于大部分的演员来说，就能称得上成功了。

图2 职业生涯长度、活跃度和产出的分布。图源：Williams等

英国伦敦玛丽王后大学的Lucas Lacasa及同事利用一个全球数据库，研究了1888年至2016年间200多万名荧幕演员的产出时间模式，发现大部分的演员在其演艺生涯当中很少有署名作品，而少数演员拥有逾100个署名作品，因此在工作分配方面呈现出“富者愈富”的现象。作者还报告表示，虽然演员在其演艺生涯中的工作时间占比不可预测，但是活跃期和沉寂期呈现出集聚现象，即如果演员在特定一年工作了，那么他们在第二年有工作的可能性更大；同样如果前一年没有工作，下一年有工作的可能性就更小。作者表示，依据演员的过往工作经历，有可能能够以85%的准确率预测一名演员的最高产年份是否已经出现。

摘要：In certain artistic endeavours—such as acting in films and TV, where unemployment rates hover at around 90%—sustained productivity (simply making a living) is probably a better proxy for quantifying success than high impact. Drawing on a worldwide database, here we study the temporal profiles of activity of actors and actresses. We show that the dynamics of job assignment is well described by a “rich-get-richer” mechanism and we find that, while the percentage of a career spent active is unpredictable, such activity is clustered. Moreover, productivity tends to be higher towards the beginning of a career and there are signals preceding the most productive year. Accordingly, we propose a machine learning method which predicts with 85% accuracy whether this “annus mirabilis” has passed, or if better days are still to come. We analyse actors and actresses separately, also providing compelling evidence of gender bias in show business.

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期刊介绍：Nature Communications (https://www.nature.com/ncomms/) is an open access journal that publishes high-quality research from all areas of the natural sciences. Papers published by the journal represent important advances of significance to specialists within each field.

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（来源：科学网）