Gender Representation in Literature: Analysis of Characters' Physical Descriptions

Abstract

This study employs Natural Language Processing (NLP) techniques to quantitatively analyze the descriptions of male and female body parts in Portuguese literature. We investigate these descriptions' frequency, specificity, and objectification by examining a corpus of literary works. The results indicate distinct differences in how male and female bodies are portrayed, revealing evidence of gender bias in the choice of specific descriptors for body parts. This research contributes to the ongoing discourse surrounding gender representation in literature, shedding light on the potential biases in textual descriptions. Furthermore, it underscores the significance of NLP techniques in uncovering patterns within literary texts, providing valuable insights into data mining. Through this analysis, we deepen our understanding of gender dynamics within literary works and foster critical discussions on representation in literature.