gendered_painting

Author: Yangyu Wang

Date: May 11. 2025

Research Intuitives

This is the coursework for MACS30200, on the gender representations in paintings.

Result Snapshots

1. Face Counts Trend

2. Female Face Proportion Trend

3. Gender Size and Obliqueness Density

4. Gender Size and Obliqueness Trend

5. Gender Gap in Size and Obliqueness

6. Trend of Gender Gap in Size and Obliqueness

Materials

Data are in data, codes are in code, and visualizations see Img. Content analysis is made upon the paintings in Painting_Example.

Requirements for running

Please run the following lines before running the code.

In terminal, please run:

pip install -r Requirements.txt

In R, please run:

source("Requirements.R")