What Contributes to Affective Polarization in Networked Online Environments? Evidence from an Agent-Based Model

TL;DR

This study tackles the mechanisms driving affective polarization in digital environments by developing an agent-based simulation with a synthetic two-party population on a directed scale-free network. It operationalizes three drivers—affective asymmetry, neighborhood composition, and elite bias—and models how exposure to partisan news via both local networks and original sources propagates through the system with parameters such as $N=10{,}000$, $|E|=10^6$, $t_f=600$, $M=10$, $\alpha\in\{1,5,10\}$, $p_e=0.01$, $p_r=1$, and $p_{re}=0.5$. The results show that affective asymmetry consistently accelerates polarization, that ideology balance within the public can increase the speed of cross-cutting exposure and polarization, and that elite composition can dampen or amplify these effects depending on alignment with the public. The findings challenge simple echo-chamber narratives by showing that polarization can intensify even with cross-cutting exposure and that elite-majoritarian configurations may temper mass polarization; they also highlight policy-relevant considerations for platform design and information diffusion. The work provides a formal framework for analyzing how micro-level exposure and affective responses aggregate to macro-level polarization in networked environments, with implications for democratic discourse and media governance.

Abstract

Affective polarization, or, inter-party hostility, is increasingly recognized as a pervasive issue in democracies worldwide, posing a threat to social cohesion. The digital media ecosystem, now widely accessible and ever-present, has often been implicated in accelerating this phenomenon. However, the precise causal mechanisms responsible for driving affective polarization have been a subject of extensive debate. While the concept of echo chambers, characterized by individuals ensconced within like-minded groups, bereft of counter-attitudinal content, has long been the prevailing hypothesis, accumulating empirical evidence suggests a more nuanced picture. This study aims to contribute to the ongoing debate by employing an agent-based model to illustrate how affective polarization is either fostered or hindered by individual news consumption and dissemination patterns based on ideological alignment. To achieve this, we parameterize three key aspects: (1) The affective asymmetry of individuals' engagement with in-party versus out-party content, (2) The proportion of in-party members within one's social neighborhood, and (3) The degree of partisan bias among the elites within the population. Subsequently, we observe macro-level changes in affective polarization within the population under various conditions stipulated by these parameters. This approach allows us to explore the intricate dynamics of affective polarization within digital environments, shedding light on the interplay between individual behaviors, social networks, and information exposure.

Figures (12)

• Figure 1: Typical news spread mechanism in a social network Note: The figure illustrates the spread of news in a social network driven by both media outlets and exposure to individual retweets. The process is assumed to be influenced by individual partisan affiliations. The light red and light green colors suggest the two predominant ideological slants.
• Figure 2: Individuals' affective response to news content by slant dissimilarity and affective asymmetry Note: The figure illustrates individuals' affective response as a function of slant dissimilarity upon exposure to news content, shown for varying levels of affective asymmetry ($\alpha$). Higher affective asymmetry ($\alpha$) results in a more pronounced affective response from individuals.
• Figure 3: Variation in mean affective polarization by affective asymmetry, population composition, and elite subgroup composition Note: The figure illustrates the variation in mean affective polarization as a function of affective asymmetry, population composition, and elite subgroup composition. The solid line in the center of the line plot denotes the mean value, while the shaded region of the same color represents the standard deviation. The increase in mean affect is most rapid when the composition of both the elite subgroup and the general population is balanced.
• Figure 4: Variation in mean in-party affect by affective asymmetry, population composition, and elite subgroup composition Note: The figure illustrates the variation in mean in-party affect as a function of affective asymmetry, population composition, and elite subgroup composition. The solid line in the center of the line plot denotes the mean value, while the shaded region of the same color represents the standard deviation. The increase in mean in-party affect is most rapid when the composition of both the elite subgroup and the general population is balanced.
• Figure 5: Variation in mean out-party affect by affective asymmetry, population composition, and elite subgroup composition Note: The figure illustrates the variation in mean out-party affect as a function of affective asymmetry, population composition, and elite subgroup composition. The solid line in the center of the line plot denotes the mean value, while the shaded region of the same color represents the standard deviation. The decrease in mean out-party affect is most rapid when the composition of both the elite subgroup and the general population is balanced.