Representations of Racial Minorities in Popular Movies: A Content-Analytic Synergy of Computer Vision and Network Science

Date created: | Last Updated:


Creating DOI. Please wait...

Create DOI

Category: Project

Description: In the Hollywood film industry, racial minorities remain underrepresented. Characters from racially underrepresented groups receive less screen time, fewer central story positions, and frequently inherit plotlines, motivations, and actions that are primarily driven by white characters. Currently, there are no clearly defined, standardized, and scalable metrics for taking stock of racial minorities’ cinematographic representation. In this paper, we combine methodological tools from computer vision and network science to develop a content analytic framework for identifying visual and structural racial biases in film productions. We apply our approach on a set of 100 popular, full-length movies, demonstrating that this method provides a scalable examination of racial inclusion in film production and predicts movie performance. We integrate our method into larger theoretical discussions on audiences’ perception of racial minorities and illuminate future research trajectories towards the computational assessment of racial biases in audiovisual narratives.


Add important information, links, or images here to describe your project.


Loading files...



Recent Activity

Loading logs...

OSF does not support the use of Internet Explorer. For optimal performance, please switch to another browser.
This website relies on cookies to help provide a better user experience. By clicking Accept or continuing to use the site, you agree. For more information, see our Privacy Policy and information on cookie use.

Start managing your projects on the OSF today.

Free and easy to use, the Open Science Framework supports the entire research lifecycle: planning, execution, reporting, archiving, and discovery.