2024/02/08 by Dima Kagan, Mor Levy, Michael Fire +1 · 1 voice
Social Sciences · Arts and Humanities · Computer Science · #Media, Gender, and Advertising #Subtitles and Audiovisual Media #Digital Media and Visual Art
paper · pdf · doi:10.1057/s41599-023-02040-y
openalex publication_date 2024/02/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Abstract In the last decades, global awareness toward the importance of diverse representation has been increasing. The 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 the US population. An automatic approach to monitoring ethnic diversity in the film industry, potentially integrated with financial value, may be of significant use for producers and policymakers.