2022 ELECTIONS IN A NUT SHELL: Political personalism and Twitter as a polarizing platform
Emotional Polarization, Political Personalism, Twitter and Politics, Topological Data Analysis (TDA), Political Communication.
his dissertation examines political narratives on Twitter during the Brazilian presidential elections of 2022, focusing on affective polarization and political personalism. The motivation for this study arises from the need to expand understanding of affective polarization in Digital Social Media and how Twitter's specific interface influences this phenomenon distinctly for each candidate. The research aims to fill existing theoretical gaps, employing Topological Data Analysis (TDA) to identify patterns of political personalism and affective polarization, contributing methodologically with new tools for analyzing large volumes of data in political communication. The dissertation's main hypothesis is that political personalism and the platform's architecture, permeated by feelings of political alienation, favor affective polarization on Twitter. The objectives include mapping networks of political personalism and affective polarization, applying TDA in the field of political communication, identifying Persistent Homologies in narrative constellations, and relating them to Brazilian politics during the 2022 elections. The research adopts a qualitative approach, analyzing a large volume of tweets collected through data scraping techniques and using the Argos code for topological and content analysis. The main results indicate the identification of Persistent Homologies and a causal relationship between political personalism and affective polarization, centered on the figures of Bolsonaro and Lula, as well as highlighting the influence of Twitter's architecture in the process.