In the last decades, global awareness towards the importance of diverse representation has been increasing. Lack of diversity and discrimination toward minorities did not skip the film industry. Here, we examine ethnic bias in the film industry through commercial posters, the industry's primary advertisement medium for decades. Movie posters are designed to establish the viewer's initial impression. We developed a novel approach for evaluating ethnic bias in the film industry by analyzing nearly 125,000 posters using state-of-the-art deep learning models. Our analysis shows that while ethnic biases still exist, there is a trend of reduction of bias, as seen by several parameters. Particularly in English-speaking movies, the ethnic distribution of characters on posters from the last couple of years is reaching numbers that are approaching the actual ethnic composition of US population. An automatic approach to monitor ethnic diversity in the film industry, potentially integrated with financial value, may be of significant use for producers and policymakers.
翻译:在过去几十年里,全球对多样性代表的重要性的认识不断提高,缺乏多样性和对少数民族的歧视并没有跳过电影业。在这里,我们通过商业海报(电影业的主要广告媒介)检查电影业的种族偏见,这几十年来一直是电影业的主要广告媒介。电影海报旨在建立观众的初步印象。我们开发了一种新颖的方法,利用最先进的深层次学习模式分析近125 000张电影业的种族偏见。我们的分析表明,虽然种族偏见仍然存在,但偏见有减少的趋势,这可以从几个参数中看出。 特别是在讲英语的电影中,过去几年里海报上人物的族裔分布达到了接近美国人口实际族裔构成的数量。 一种自动的方法来监测电影业中的族裔多样性,有可能与经济价值相结合。 对于制片者和决策者来说,一种可能非常有用的方法。