The emergence and perils of polarization

Social identity correlates of social media engagement before and after the 2022 Russian invasion of Ukraine

Despite the global presence of social media platforms, the reasons why people like and share content are still poorly understood. We investigate how group identity mentions and expressions of ingroup solidarity and outgroup hostility in posts correlate with engagement on Ukrainian social media (i.e., shares, likes, and other reactions) before and after the 2022 Russian invasion of Ukraine. We use a dataset of 1.6 million posts from Ukrainian news source pages on Facebook and Twitter (currently X) and a geolocated sample of 149 thousand Ukrainian tweets. Before the 2022 Russian invasion, we observe that outgroup mentions in posts from news source pages are generally more strongly associated with engagement than negative, positive, and moral-emotional language. After the invasion, social identity mentions become less strongly associated with engagement. Moreover, post-invasion ingroup solidarity posts are strongly related to engagement, whereas posts expressing outgroup hostility show smaller associations. This is the case for both news and non-news social media data. Our correlational results suggest that signaling solidarity with one's ingroup online is associated with more engagement than negativity about outgroups during intense periods of intergroup conflicts, at least in the context of the Russian-Ukrainian war.

How the manner in which data is visualized affects and corrects (mis)perceptions of political polarization

While the mechanisms underlying polarization are complex, scholars have consistently found a pervasive overestimation of perceptions of polarization to be a contributing factor. We argue that one mitigation strategy that can work at scale to address such misperceptions might be relatively straightforward: better data visualizations of cross-party attitudes on key issues. In a large-scale (N = 6603), international replication, we find that mode of presentation-or the manner in which data are visually presented-plays a significant role in moderating perceptions of polarization, even for longstanding, divisive issues for which partisans would likely hold strong prior beliefs. Additionally, we find the effects that different modes of presentation have on issue-specific polarization also extend to participant beliefs about overall interparty polarization, with certain modes proving capable of not only promoting less polarized views but also enabling more accurate estimates of the extent to which political groups agree. Finally, our findings also suggest that the manner in which intergroup data are visualized may also exert influence over the degree to which political groups are essentialized-a finding with implications for not only political perception but also for apolitical social psychological phenomena such as dehumanization.

Collective group drift in a partial-differential-equation-based opinion dynamics model with biased perception kernels

In the age of technology, individuals accelerate their biased gathering of information, which in turn leads to a population becoming extreme and more polarized. Here we study a partial-differential-equation model for opinion dynamics that exhibits collective behavior subject to nonlocal interactions. We developed an interaction kernel function to represent biased information gathering. Through a linear stability analysis, we show that biased populations can still form opinionated groups. However, a population that is too heavily biased can no longer come to a consensus, that is, the initial homogeneous mixed state becomes stable. Numerical simulations with biased information gathering show the ability for groups to collectively drift towards one end of the opinion space. This means that a small bias in each individual will collectively lead to groups of individuals becoming extreme together. The characteristic time scale for a group's existence is captured from numerical experiments using the temporal correlation function. Supplementing this, we included a measure of how different each population is after regular time intervals using a form of the Manhattan and Euclidean distance metrics. We conclude by exploring how wall boundary conditions induce pattern formation initially on the most extreme sides of the domain.

Understanding political divisiveness using online participation data from the 2022 French and Brazilian presidential elections

Digital technologies can augment civic participation by facilitating the expression of detailed political preferences. Yet, digital participation efforts often rely on methods optimized for elections involving a few candidates. Here we present data collected in an online experiment where participants built personalized government programmes by combining policies proposed by the candidates of the 2022 French and Brazilian presidential elections. We use this data to explore aggregates complementing those used in social choice theory, finding that a metric of divisiveness, which is uncorrelated with traditional aggregation functions, can identify polarizing proposals. These metrics provide a score for the divisiveness of each proposal that can be estimated in the absence of data on the demographic characteristics of participants and that explains the issues that divide a population. These findings suggest that divisiveness metrics can be useful complements to traditional aggregation functions in direct forms of digital participation.

Transformation of social relationships in COVID-19 America: Remote communication may amplify political echo chambers

The COVID-19 pandemic, with millions of Americans compelled to stay home and work remotely, presented an opportunity to explore the dynamics of social relationships in a predominantly remote world. Using the 1972-2022 General Social Surveys, we found that the pandemic significantly disrupted the patterns of social gatherings with family, friends, and neighbors but only momentarily. Drawing from the nationwide ego-network surveys of 41,033 Americans from 2020 to 2022, we found that the size and composition of core networks remained stable, although political homophily increased among nonkin relationships compared to previous surveys between 1985 and 2016. Critically, heightened remote communication during the initial phase of the pandemic was associated with increased interaction with the same partisans, although political homophily decreased during the later phase of the pandemic when in-person contacts increased. These results underscore the crucial role of social institutions and social gatherings in promoting spontaneous encounters with diverse political backgrounds.

Social Depolarization and Diversity of Opinions-Unified ABM Framework

Most sociophysics opinion dynamics simulations assume that contacts between agents lead to greater similarity of opinions, and that there is a tendency for agents having similar opinions to group together. These mechanisms result, in many types of models, in significant polarization, understood as separation between groups of agents having conflicting opinions. The addition of inflexible agents (zealots) or mechanisms, which drive conflicting opinions even further apart, only exacerbates these polarizing processes. Using a universal mathematical framework, formulated in the language of utility functions, we present novel simulation results. They combine polarizing tendencies with mechanisms potentially favoring diverse, non-polarized environments. The simulations are aimed at answering the following question: How can non-polarized systems exist in stable configurations? The framework enables easy introduction, and study, of the effects of external "pro-diversity", and its contribution to the utility function. Specific examples presented in this paper include an extension of the classic square geometry Ising-like model, in which agents modify their opinions, and a dynamic scale-free network system with two different mechanisms promoting local diversity, where agents modify the structure of the connecting network while keeping their opinions stable. Despite the differences between these models, they show fundamental similarities in results in terms of the existence of low temperature, stable, locally and globally diverse states, i.e., states in which agents with differing opinions remain closely linked. While these results do not answer the socially relevant question of how to combat the growing polarization observed in many modern democratic societies, they open a path towards modeling polarization diminishing activities. These, in turn, could act as guidance for implementing actual depolarization social strategies.

Quantifying ideological polarization on a network using generalized Euclidean distance

An intensely debated topic is whether political polarization on social media is on the rise. We can investigate this question only if we can quantify polarization, by taking into account how extreme the opinions of the people are, how much they organize into echo chambers, and how these echo chambers organize in the network. Current polarization estimates are insensitive to at least one of these factors: They cannot conclusively clarify the opening question. Here, we propose a measure of ideological polarization that can capture the factors we listed. The measure is based on the generalized Euclidean distance, which estimates the distance between two vectors on a network, e.g., representing people's opinion. This measure can fill the methodological gap left by the state of the art and leads to useful insights when applied to real-world debates happening on social media and to data from the U.S. Congress.

Social asset or social liability? How partisanship moderates the relationship between social capital and Covid-19 vaccination rates across United States counties

This study investigates the interactive effect of social capital and partisanship on COVID-19 vaccination rates. Using county-level data from the United States (U.S.), we empirically find that social capital is a double-edged sword. Its effect on the vaccination rate depends on the dominant partisanship of the jurisdiction. In more liberal counties, stronger social capital is a social asset that encourages people to seek vaccination and results in a higher vaccination rate. In contrast, in more conservative counties where the Trump-voting rate reaches 73% and beyond, stronger social capital becomes a social liability for public health by reinforcing residents' hesitancy toward or rejection of vaccinations, leading to a lower vaccination rate. This study implies the need for reducing the partisanship salience and investing in bridging and linking social capital in polarized communities.

Cognitive-motivational mechanisms of political polarization in social-communicative contexts

Healthy democratic polities feature competing visions of a good society but also require some level of cooperation and institutional trust. Democracy is at risk when citizens become so polarized that an 'us versus them' mentality dominates. Despite a vast multidisciplinary literature, no coherent conceptual framework of the microlevel dynamics that increase or decrease polarization has been presented. In this Review, we provide a conceptual framework to integrate scientific knowledge about cognitive-motivational mechanisms that influence political polarization and the social-communicative contexts in which they are enacted. Ego-justifying and group-justifying motives lead individuals to defend their own pre-existing beliefs and those of their in-group, respectively. However, a distinct class of system-justifying motives contributes to asymmetric forms of polarization. Whereas conservative-rightist ideology is associated with valuing tradition, social order and maintenance of the status quo, liberal-leftist ideology is associated with a push for egalitarian social change. These cognitive-motivational mechanisms interact with social influence processes linked to communication source, message and channel factors, all of which might contribute to increased or decreased polarization. We conclude with a discussion of unanswered questions and ways in which our framework can be extended to the study of culture and institutions.