Image analysis to automatically quantify gender bias in movies

October 17, 2019

Many commercial films worldwide continue to express womanhood in a stereotypical manner, a recent study using image analysis showed. A KAIST research team developed a novel image analysis method for automatically quantifying the degree of gender bias in in films.

The 'Bechdel Test' has been the most representative and general method of evaluating gender bias in films. This test indicates the degree of gender bias in a film by measuring how active the presence of womenis in a film. A film passes the Bechdel Test if the film (1) has at least two female characters, (2) who talk to each other, and (3) their conversation is not related to the male characters.

However, the Bechdel Test has fundamental limitations regarding the accuracy and practicality of the evaluation. Firstly, the Bechdel Test requires considerable human resources, as it is performed subjectively by a person. More importantly, the Bechdel Test analyzes only a single aspect of the film, the dialogues between characters in the script, and provides only a dichotomous result of passing the test, neglecting the fact that a film is a visual art form reflecting multi-layered and complicated gender bias phenomena. It is also difficult to fully represent today's various discourse on gender bias, which is much more diverse than in 1985 when the Bechdel Test was first presented.

Inspired by these limitations, a KAIST research team led by Professor Byungjoo Lee from the Graduate School of Culture Technology proposed an advanced system that uses computer vision technology to automatically analyzes the visual information of each frame of the film. This allows the system to more accurately and practically evaluate the degree to which female and male characters are discriminatingly depicted in a film in quantitative terms, and further enables the revealing of gender bias that conventional analysis methods could not yet detect.

Professor Lee and his researchers Ji Yoon Jang and Sangyoon Lee analyzed 40 films from Hollywood and South Korea released between 2017 and 2018. They downsampled the films from 24 to 3 frames per second, and used Microsoft's Face API facial recognition technology and object detection technology YOLO9000 to verify the details of the characters and their surrounding objects in the scenes.

Using the new system, the team computed eight quantitative indices that describe the representation of a particular gender in the films. They are: emotional diversity, spatial staticity, spatial occupancy, temporal occupancy, mean age, intellectual image, emphasis on appearance, and type and frequency of surrounding objects.

According to the emotional diversity index, the depicted women were found to be more prone to expressing passive emotions, such as sadness, fear, and surprise. In contrast, male characters in the same films were more likely to demonstrate active emotions, such as anger and hatred.

The type and frequency of surrounding objects index revealed that female characters and automobiles were tracked together only 55.7 % as much as that of male characters, while they were more likely to appear with furniture and in a household, with 123.9% probability.

In cases of temporal occupancy and mean age, female characters appeared less frequently in films than males at the rate of 56%, and were on average younger in 79.1% of the cases. These two indices were especially conspicuous in Korean films.

Professor Lee said, "Our research confirmed that many commercial films depict women from a stereotypical perspective. I hope this result promotes public awareness of the importance of taking prudence when filmmakers create characters in films."
-end-
This study was supported by KAIST College of Liberal Arts and Convergence Science as part of the Venture Research Program for Master's and PhD Students, and will be presented at the 22nd ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW) on November 11 to be held in Austin, Texas.

The Korea Advanced Institute of Science and Technology (KAIST)

Related Gender Bias Articles from Brightsurf:

You drive like a girl: Study shows gender bias in perceptions of ride-sharing performance
While digital brokerages provide a more efficient method for the exchange of goods and services and an improved way for consumers to voice their opinions about the quality of work they receive, bias and discrimination can emerge as part of the review process, according to Notre Dame research.

UMBC study reveals gender bias in bird song research and impact of women on science
A new paper has found that women are more likely than men to be authors, and even more likely to be first authors, of research papers about female bird song.

Gender bias in evaluating surgical residency faculty members may be decreasing
In the male-dominated field of surgery, female faculty of training programs tend to receive lower scores than male faculty on their teaching evaluations, which are important for career advancement, past research has found.

Even when women outnumber men, gender bias persists among science undergrads
Increasing gender diversity has been a long-sought goal across many of the sciences, and interventions and programs to attract more women into fields like physics and math often happen at the undergraduate level.

Gender bias kept alive by people who think it's dead
Workplace gender bias is being kept alive by people who think it's no longer an issue, new research suggests.

Sex bias in pain research
Most pain research remains overwhelmingly based on the study of male rodents, continuing to test hypotheses derived from earlier experiments on males.

Effects of gender bias, stereotypes in surgical training
This randomized clinical trial investigated the association between pro-male gender bias and negative stereotypes against women during surgical residency on surgical skills and proactive career development of residents in general surgery training programs.

Gender bias in commenting poses barriers to women scholars: York University sociologist
Women academics are less likely than men to comment on published research, limiting scholarly debate, a new study co-authored by York University sociologist Professor Cary Wu, shows.

Earliest age gender dysphoria experienced by transgender adults seeking gender-affirming surgery
Data collected from 155 adult transgender women and 55 transgender men were used to identify the earliest age at which gender dysphoria was experienced in this patient population seeking genital gender-affirming surgery at a California hospital.

Scientists can see the bias in your brain
The strength of alpha brain waves reveals if you are about to make a biased decision, according to research recently published in JNeurosci.

Read More: Gender Bias News and Gender Bias Current Events
Brightsurf.com is a participant in the Amazon Services LLC Associates Program, an affiliate advertising program designed to provide a means for sites to earn advertising fees by advertising and linking to Amazon.com.