Department of Computer Architecture and Technology, University of Granada, Granada, Spain.
Department of Computer Science and Engineering, University of Cádiz, Cádiz, Spain.
PLoS One. 2021 Mar 31;16(3):e0248881. doi: 10.1371/journal.pone.0248881. eCollection 2021.
Creating a story is a challenging task due to the the complex relations between the parts that make it up, which is why many new stories are built on those cohesive elements or patterns, called tropes that have been shown to work in the past. A trope is a recurring storytelling device or pattern, or sometimes a meta-element, used by the authors to express ideas that the audience can recognize or relate to, such as the Hero's Journey. Discovering tropes and how they cluster in popular works and doing it at scale to generate new plots may benefit writers; in this paper, we analyze them and use a principled procedure to identify trope combinations, or communities, that could possible be successful. The degree of development of these different communities can help us identify areas that are under-developed and, thus, susceptible to such a type of development. To detect these communities, with their associated degree of development and interest, we propose a methodology based on scientometric and complex network analysis techniques. As a secondary objective, we will obtain a general perspective in the trope and films network: the tropesphere. We have used a dataset of 10,766 movies and 25,776 tropes associated with them, together with rating, genres and popularity. Our analysis has shown that not only there are different trope communities associated with specific genres, and that there are significant differences between the rating and popularity of these communities but also there are differences on the level of development between them: emerging/declining, specific, transversal or motor.
创作故事是一项具有挑战性的任务,因为构成故事的各个部分之间存在着复杂的关系。这就是为什么许多新故事都是基于那些过去被证明有效的连贯元素或模式,即所谓的“隐喻”构建的。隐喻是一种反复出现的叙事手段或模式,或者有时是一个元元素,作者用它来表达观众可以识别或联想到的想法,比如英雄之旅。发现隐喻以及它们在流行作品中是如何聚集的,并在大规模地进行以生成新情节,这可能对作家有帮助;在本文中,我们分析了隐喻,并使用一种有原则的程序来识别可能成功的隐喻组合或社区。这些不同社区的发展程度可以帮助我们识别那些不发达的领域,从而容易受到这种类型的发展影响。为了检测这些社区及其相关的发展程度和兴趣,我们提出了一种基于科学计量和复杂网络分析技术的方法。作为次要目标,我们将在隐喻和电影网络中获得一个总体视角:隐喻宇宙。我们使用了一个包含 10766 部电影和 25776 个与之相关的隐喻的数据集,以及评分、类型和流行度。我们的分析表明,不仅存在与特定类型相关的不同隐喻社区,而且这些社区的评分和流行度之间存在显著差异,此外,它们之间的发展水平也存在差异:新兴/衰落、特定、横向或动力。