Visual Representation and Stereotypes in News Media

46 Pages Posted: 15 Apr 2022

See all articles by Elliott Ash

Elliott Ash

ETH Zürich

Ruben Durante

Universitat Pompeu Fabra

Maria Grebenshchikova

Center for Digital Technology and Management; Technical University of Munich

Carlo Schwarz

Bocconi University - Department of Economics

Multiple version iconThere are 3 versions of this paper

Date Written: 2022

Abstract

We propose a new method for measuring gender and ethnic stereotypes in news reports. By combining computer vision and natural language processing tools, the method allows us to analyze both images and text as well as the interaction between the two. We apply this approach to over 2 million web articles published in the New York Times and Fox News between 2000 and 2020. We find that in both outlets, men and whites are generally over-represented relative to their population share, while women and Hispanics are under-represented. We also document that news content perpetuates common stereotypes such as associating Blacks and Hispanics with low-skill jobs, crime, and poverty, and Asians with high-skill jobs and science. For jobs, we show that the relationship between visual representation and racial stereotypes holds even after controlling for the actual share of a group in a given occupation. Finally, we find that group representation in the news is influenced by the gender and ethnic identity of authors and editors.

Keywords: stereotypes, gender, race, media, computer vision, text analysis

JEL Classification: L820, J150, J160, Z100, C450

Suggested Citation

Ash, Elliott and Durante, Ruben and Grebenshchikova, Mariia and Schwarz, Carlo, Visual Representation and Stereotypes in News Media (2022). CESifo Working Paper No. 9686, Available at SSRN: https://ssrn.com/abstract=4082591 or http://dx.doi.org/10.2139/ssrn.4082591

Elliott Ash (Contact Author)

ETH Zürich ( email )

Rämistrasse 101
ZUE F7
Zürich, 8092
Switzerland

Ruben Durante

Universitat Pompeu Fabra ( email )

Ramon Trias Fargas, 25-27
Barcelona, E-08005
Spain

Mariia Grebenshchikova

Center for Digital Technology and Management ( email )

Munich
Germany

Technical University of Munich ( email )

Arcisstrasse 21
Munich, DE 80333
Germany

Carlo Schwarz

Bocconi University - Department of Economics ( email )

Via Gobbi 5
Milan, 20136
Italy

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