Work

Gender Stereotypes in Hollywood Movies and Their Evolution over Time: Insights from Network Analysis

Year: 2022

Type: article

Abstract: The present analysis of more than 180,000 sentences from movie plots across the period from 1940 to 2019 emphasizes how gender stereotypes are expressed through the cultural products of society. By applying a network analysis to the word co-occurrence networks of movie plots and using a novel method of identifying story tropes, we demonstrate that gender stereotypes exist in Hollywood movies. An analysis of specific paths in the network and the words reflecting various domains show the dynamic changes in some of these stereotypical associations. Our results suggest that gender stereotypes are complex and dynamic in nature. Specifically, whereas male characters appear to be associated with a diversity of themes in movies, female characters seem predominantly associated with the theme of romance. Although associations of female characters to physical beauty and marriage are declining over time, associations of female characters to sexual relationships and weddings are increasing. Our results demonstrate how the application of cognitive network science methods can enable a more nuanced investigation of gender stereotypes in textual data.

Source: Big Data and Cognitive Computing

DOI: 10.3390/bdcc6020050

Authors: Arjun M. Kumar, Jasmine Y. Q. Goh, Tiffany H. H. Tan, Cynthia S. Q. Siew

Institution: National University of Singapore

Language: English

Topic: Media, Gender, and Advertising

Subfield: Gender Studies

Field: Social Sciences

Domain: Social Sciences

SDG: Gender equality

Open Access status: gold

Estimated APC paid: $1,466