Quantifying the Spread of Online Incivility in Brazilian Politics

TL;DR

The paper develops a multidimensional framework for online incivility (Impoliteness, Physical Harm and Violent Political Rhetoric, Hate Speech and Stereotyping, and Threats to Democratic Institutions and Values) and applies it to roughly 5 million tweets from 2,307 Brazilian political influencers during the 2022 election. Through manual annotation, active-learning classifiers, smoothing splines, quantile regression, and multilayer network analysis, the study characterizes temporal dynamics, disseminators, audiences, and information-flow mechanisms of incivility. Key findings include the predominance of left‑aligned individual influencers in spreading incivility, distinct temporal patterns across dimensions (with IMP peaking during campaigns and other dimensions tied to violent events), and a diffusion pattern that integrates direct and mixed information flows more than classic two‑step models. The results offer a robust conceptual and methodological framework that can be extended to other political contexts and platforms, with implications for understanding echo chambers and democratic resilience in online discourse.

Abstract

Incivility refers to behaviors that violate collective norms and disrupt cooperation within the political process. Although large-scale online data and automated techniques have enabled the quantitative analysis of uncivil discourse, prior research has predominantly focused on impoliteness or toxicity, often overlooking other behaviors that undermine democratic values. To address this gap, we propose a multidimensional conceptual framework encompassing Impoliteness, Physical Harm and Violent Political Rhetoric, Hate Speech and Stereotyping, and Threats to Democratic Institutions and Values. Using this framework, we measure the spread of online political incivility in Brazil using approximately 5 million tweets posted by 2,307 political influencers during the 2022 Brazilian general election. Through statistical modeling and network analysis, we examine the dynamics of uncivil posts at different election stages, identify key disseminators and audiences, and explore the mechanisms driving the spread of uncivil information online. Our findings indicate that impoliteness is more likely to surge during election campaigns. In contrast, the other dimensions of incivility are often triggered by specific violent events. Moreover, we find that left-aligned individual influencers are the primary disseminators of online incivility in the Brazilian Twitter/X sphere and that they disseminate not only direct incivility but also indirect incivility when discussing or opposing incivility expressed by others. They relay those content from politicians, media agents, and individuals to reach broader audiences, revealing a diffusion pattern mixing the direct and two-step flows of communication theory. This study offers new insights into the multidimensional nature of incivility in Brazilian politics and provides a conceptual framework that can be extended to other political contexts.

Figures (10)

• Figure 1: Multi-dimensional conceptualization of incivility and its related concepts. Broadly speaking, incivility encompasses both impoliteness and intolerance, and toxicity overlaps with both concepts.
• Figure 2: Procedure for creating the positive (uncivil) samples with active learning.
• Figure 3: Motifs of information flow mechanisms.
• Figure 4: Trends and events dynamics of four incivility dimensions—IMP, PHAVPR, HSST, and THREAT. The first and third columns show trends with smoothing splines ($\lambda$=0.6). Original data points with GCV smoothing splines and outliers (red dots) identified by approximate Cook's distance are in the second and fourth columns. Grey lines mark five key events: (1) First-round election, (2) Run-off election, (2) Brasília protest, (3) Highway blockades, and (4) Congress attack.
• Figure 5: Kernel density estimate plot of the variation in survey audience's exposure, measured by the total number of followers and retweet receivers of uncivil messages, as the ratio of uncivil posts (density) increases.