ARC Centre of Excellence for Mathematical & Statistical Frontiers (ACEMS), School of Mathematical Sciences, University of Adelaide, Australia.
PLoS One. 2020 Feb 26;15(2):e0223833. doi: 10.1371/journal.pone.0223833. eCollection 2020.
The number of characters in a movie is an important feature. However, it is non-trivial to measure directly, for example naive metrics such as the number of credited characters vary wildly. Here, we show that a metric based on the notion of ecological diversity as expressed through a Shannon-entropy based metric can characterise the number of characters in a movie, and is useful in taxonomic classification. We also show how the metric can be generalised using Jensen-Shannon divergence to provide a measure of the similarity of characters appearing in different movies, for instance of use in recommendation systems, e.g., Netflix. We apply our measures to the Marvel Cinematic Universe (MCU), and show what they teach us about this highly successful franchise of movies. In particular, these measures provide a useful predictor of success for films in the MCU, as well as a natural means to understand the relationships between the stories in the overall film arc.
电影中的角色数量是一个重要特征。然而,直接测量并非易事,例如,简单地统计有字幕的角色数量会有很大的差异。在这里,我们展示了一种基于生态多样性概念的度量方法,这种度量方法可以通过基于香农熵的度量来表示,可以用于电影角色的分类。我们还展示了如何使用 Jensen-Shannon 散度将该度量方法推广到不同电影中出现的角色的相似性度量,例如在推荐系统中的应用,例如 Netflix。我们将这些度量方法应用于漫威电影宇宙(MCU),并展示了它们可以告诉我们关于这个非常成功的电影系列的什么信息。特别是,这些度量方法为 MCU 中的电影提供了一个有用的成功预测指标,以及一种理解整体电影弧中故事之间关系的自然方法。