Gender representation in mass media has long been mainly studied by qualitatively analyzing content. This article illustrates how automated computational methods may be used in this context to scale up such empirical observations and increase their resolution and significance. We specifically apply a face and gender detection algorithm on a broad set of popular movies spanning more than three decades to carry out a large-scale appraisal of the on-screen presence of women and men. Beyond the confirmation of a strong under-representation of women, we exhibit a clear temporal trend towards a fairer representativeness. We further contrast our findings with respect to movie genre, budget, and various audience-related features such as movie gross and user ratings. We lastly propose a fine description of significant asymmetries in the mise-en-sc\`ene and mise-en-cadre of characters in relation to their gender and the spatial composition of a given frame.
翻译:长期以来,主要通过定性分析内容对大众媒体中的性别代表性进行了研究,这篇文章说明了在这方面如何使用自动计算方法来扩大这种经验性观察,并增加其分辨率和重要性,我们特别对30多年的一大批流行电影采用面孔和性别检测算法,对男女在屏幕上的存在进行大规模评估,除了证实妇女代表性严重不足外,我们还表现出明显的时间趋势,走向更公平的代表性。我们进一步对比了我们在电影类型、预算和各种观众相关特征,如电影毛值和用户评级方面的调查结果。我们最后提出一个精细的描述,说明男女在性别上和特定框架的空间构成方面人格的重大不对称。