🤖 AI Summary
This study challenges the conventional left–right binary paradigm dominating research on online political selective exposure. Drawing on survey data and Twitter activity from Brazil’s 2022 presidential election, it empirically identifies a hierarchical community structure underlying selective exposure—previously unobserved. Methodologically, the study integrates representative social surveys, multi-resolution community detection algorithms, and multivariate regression analyses across granularities. Results reveal pronounced heterogeneity in drivers: at coarse granularity, only ideological positioning exerts significant influence; at fine granularity, 189 variables—including demographics, news consumption frequency, and perceived incivility—attain statistical significance. The findings demonstrate that single-scale measurement obscures the mechanistic complexity of selective exposure. Consequently, the paper proposes a “multi-scale selective exposure” analytical framework, offering both a novel theoretical lens and a methodological benchmark for investigating cognitive segregation in digital political communication.
📝 Abstract
Selective exposure, individuals' inclination to seek out information that supports their beliefs while avoiding information that contradicts them, plays an important role in the emergence of polarization. In the political domain, selective exposure is usually measured on a left-right ideology scale, ignoring finer details. Here, we combine survey and Twitter data collected during the 2022 Brazilian Presidential Election and investigate selective exposure patterns between the survey respondents and political influencers. We analyze the followship network between survey respondents and political influencers and find a multilevel community structure that reveals a hierarchical organization more complex than a simple split between left and right. Moreover, depending on the level we consider, we find different associations between network indices of exposure patterns and 189 individual attributes of the survey respondents. For example, at finer levels, the number of influencer communities a survey respondent follows is associated with several factors, such as demographics, news consumption frequency, and incivility perception. In comparison, only their political ideology is a significant factor at coarser levels. Our work demonstrates that measuring selective exposure at a single level, such as left and right, misses important information necessary to capture this phenomenon correctly.