Mensagens de Ódio Recebidas por Candidatas Negras e Brancas Durante as Eleições no Brasil de 2022 e suas Implicações

Abstract

Based on the existing literature on political gender violence, this article seeks to deepen analyses regarding specific violence experienced by women in politics over the internet from a racial perspective. This study analyses online hatred against three black and brown candidates (hereafter referred to as “black”) and three white candidates running as federal deputies for left-wing parties during the 2022 Brazilian electoral campaign period on Twitter. The comparison between the acts of violence starts from an intersectional perspective, bringing the relationality between gender and race to the centre of this article. Based on a methodology involving deductive mixed methods, tweets tagging the six female candidates were first extracted with a subsequent measure of the level of toxicity of these comments using Google’s API tool. Afterwards, a sample of the comments was randomly selected aimed at qualitatively verifying the robustness of the categorization made by the learning machine tool. Such analysis indicated that the tool was not able to fully capture the comments’ full spectrum of toxicity, which corroborates previous considerations from the literature that these technologies lack greater linguistic diversity beyond the English
language. Furthermore, our results show that black women receive more hate both in terms of quantity and quality (as they combine misogyny and racism), suggesting that political gender-based violence is an even more robust barrier to these women being elected. Such findings point to the need for measures to address gendered political violence that also address racism.