Online Misogyny Against Female Candidates in the 2022 Brazilian Elections: A Threat to Women's Political Representation?

TL;DR

This study analyzes 10 million tweets to understand how online misogyny impacts female political candidates in Brazil's 2022 elections, revealing that increased misogynistic attacks reduce their online activity and threaten women's political participation.

Contribution

It introduces a machine learning approach to detect Portuguese misogynistic tweets and quantitatively links online hate to reduced political engagement by female candidates.

Findings

More attacks target young, left-wing, and highly visible candidates.

Increased misogynistic tweets lead to decreased candidate activity.

Online misogyny potentially silences women's voices in politics.

Abstract

Technology-facilitated gender-based violence has become a global threat to women's political representation and democracy. Understanding how online hate affects its targets is thus paramount. We analyse 10 million tweets directed at female candidates in the Brazilian election in 2022 and examine their reactions to online misogyny. Using a self-trained machine learning classifier to detect Portuguese misogynistic tweets and a quantitative analysis of the candidates' tweeting behaviour, we investigate how the number of misogynistic attacks received alters the online activity of the female candidates. We find that young and left-wing candidates and candidates with higher visibility online received significantly more attacks. Furthermore, we find that an increase in misogynistic attacks in the previous week is associated with a decrease in female candidates' tweets in the following week. This potentially threatens their equal participation in public opinion building and silences women's voices in political discourse.