Uma análise de memes ofensivos e de cunho político no contexto da eleição brasileira de 2022

Abstract

This dissertation analyzes 400 offensive political memes shared during the 2022 Brazilian electoral period on the social media platform X (formerly Twitter). In addition to investigating the discursive dynamics present in these contents, the study proposes a methodological update for the analysis of offensive political memes by incorporating specific categories of political attack into the taxonomy traditionally used in this type of research. The objective is to understand how these memes, particularly those focused on the Brazilian political scenario, seek to validate their respective ideologies by discrediting opponents and delegitimizing opposing discourses through offense. The research considers memes as multimodal discursive and cultural artifacts embedded within the context of contemporary digital culture and, at the same time, is grounded in an Information Science perspective that understands information as a thing, treating memes as documents. From this perspective, memes cease to be merely ephemeral content and instead become evidence of knowledge, values, and cultural and political practices shared by social groups. Initially, a theoretical review was conducted tracing the shift in the concept of the meme from its origins in memetic theory to its appropriation by communication and digital culture studies in the form of called internet memes. Following this review, the characteristics of the database used were presented, and the curation procedures guiding the analytical construction were described, including the stages of classification and cataloging of the memes. For the analysis, a typological content model was initially adopted, classifying political memes according to three main categories subdivided into twelve subcategories. The empirical analysis, however, revealed limitations in this taxonomy when it became necessary to capture certain forms of attack present in the corpus. In response to this limitation, the research proposed an update to the analytical model, incorporating new categories related to political attack strategies, namely accusation, morality, fake news, and violence. The results demonstrate significant discursive differences between the political spectrums analyzed: while memes associated with the left tend to concentrate on strategies of ridicule, political humor, and symbolic moralization, memes linked to the right show a higher incidence of accusation and content classified as fake news. This expansion makes it possible to refine the analysis of offensive political memes, more accurately understand the discursive dynamics involved in the circulation of such content in digital environments and offer methodological contributions for future studies on digital political communication, participatory culture, and meme analysis.