Political sectarianism in America

Understanding the rationales and information environments for early, late, and nonadopters of the COVID-19 vaccine

Anti-vaccine sentiment during the COVID-19 pandemic grew at an alarming rate, leaving much to understand about the relationship between people's vaccination status and the information they were exposed to. This study investigated the relationship between vaccine behavior, decision rationales, and information exposure on social media over time. Using a cohort study that consisted of a nationally representative survey of American adults, three subpopulations (early adopters, late adopters, and nonadopters) were analyzed through a combination of statistical analysis, network analysis, and semi-supervised topic modeling. The main reasons Americans reported choosing to get vaccinated were safety and health. However, work requirements and travel were more important for late adopters than early adopters (95% CI on OR of [0.121, 0.453]). While late adopters' and nonadopters' primary reason for not getting vaccinated was it being too early, late adopters also mentioned safety issues more often and nonadopters mentioned government distrust (95% CI on OR of [0.125, 0.763]). Among those who shared Twitter/X accounts, early adopters and nonadopters followed a larger fraction of highly partisan political accounts compared to late adopters, and late adopters were exposed to more neutral and pro-vaccine messaging than nonadopters. Together, these findings suggest that the decision-making process and the information environments of these subpopulations have notable differences, and any online vaccination campaigns need to consider these differences when attempting to provide accurate vaccine information to all three subpopulations.

Ideological self-selection in online news exposure: Evidence from Europe and the US

Today's high-choice digital media environments allow citizens to completely refrain from online news exposure and, if they do use news, to select sources that align with their ideological preferences. Yet due to measurement problems and cross-country differences, recent research has been inconclusive regarding the prevalence of ideological self-selection into like-minded online news. We introduce a multi-method design combining the web-browsing histories and survey responses of more than 7000 participants from six major democracies with supervised text classification to separate political from nonpolitical news exposure. We find that political online news exposure is both substantially less prevalent and subject to stronger ideological self-selection than nonpolitical online news exposure, especially in the United States. By highlighting the peculiar role of political news content, the results improve the understanding of online news exposure and the role of digital media in democracy.

Understanding anti-immigration sentiment spreading on Twitter

Immigration is one of the most salient topics in public debate. Social media heavily influences opinions on immigration, often sparking polarized debates and offline tensions. Studying 220,870 immigration-related tweets in the UK, we assessed the extent of polarization, key content creators and disseminators, and the speed of content dissemination. We identify a high degree of online polarization between pro and anti-immigration communities. We found that the anti-migration community is small but denser and more active than the pro-immigration community with the top 1% of users responsible for over 23% of anti-immigration tweets and 21% of retweets. We also discovered that anti-immigration content spreads also 1.66 times faster than pro-immigration messages and bots have minimal impact on content dissemination. Our findings suggest that identifying and tracking highly active users could curb anti-immigration sentiment, potentially easing social polarization and shaping broader societal attitudes toward migration.

Partisans process policy-based and identity-based messages using dissociable neural systems

Political partisanship is often conceived as a lens through which people view politics. Behavioral research has distinguished two types of "partisan lenses"-policy-based and identity-based-that may influence peoples' perception of political events. Little is known, however, about the mechanisms through which partisan discourse appealing to policy beliefs or targeting partisan identities operate within individuals. We addressed this question by collecting neuroimaging data while participants watched videos of speakers expressing partisan views. A "partisan lens effect" was identified as the difference in neural synchrony between each participant's brain response and that of their partisan ingroup vs. outgroup. When processing policy-based messaging, a partisan lens effect was observed in socio-political reasoning and affective responding brain regions. When processing negative identity-based attacks, a partisan lens effect was observed in mentalizing and affective responding brain regions. These data suggest that the processing of political discourse that appeals to different forms of partisanship is supported by related but distinguishable neural-and therefore psychological-mechanisms, which may have implications for how we characterize partisanship and ameliorate its deleterious impacts.

Three roots of online toxicity: disembodiment, accountability, and disinhibition

Online communication is central to modern social life, yet it is often linked to toxic manifestations and reduced well-being. How and why online communication enables these toxic social effects remains unanswered. In this opinion, we propose three roots of online toxicity: disembodiment, limited accountability, and disinhibition. We suggest that virtual disembodiment results in a chain of psychological states primed for deleterious social interaction. Drawing from differences between face-to-face and online interactions, the framework highlights and addresses the fundamental problems that result in impaired communication between individuals and explicates its effects on social toxicity online.

Why Twitter Sometimes Rewards What Most People Disapprove of: The Case of Cross-Party Political Relations

Recent evidence has shown that social-media platforms like Twitter (now X) reward politically divisive content, even though most people disapprove of interparty conflict and negativity. We document this discrepancy and provide the first evidence explaining it, using tweets by U.S. Senators and American adults' responses to them. Studies 1a and 1b examined 6,135 such tweets, finding that dismissing tweets received more Likes and Retweets than tweets that engaged constructively with opponents. In contrast, Studies 2a and 2b (N = 856; 1,968 observations) revealed that the broader public, if anything, prefers politicians' engaging tweets. Studies 3 (N = 323; 4,571 observations) and 4 (N = 261; 2,610 observations) supported two distinct explanations for this disconnect. First, users who frequently react to politicians' tweets are an influential yet unrepresentative minority, rewarding dismissing posts because, unlike most people, they prefer them. Second, the silent majority admit that they too would reward dismissing posts more, despite disapproving of them. These findings help explain why popular online content sometimes distorts true public opinion.

Not our kind of crowd! How partisan bias distorts perceptions of political bots on Twitter (now X)

Social bots, employed to manipulate public opinion, pose a novel threat to digital societies. Existing bot research has emphasized technological aspects while neglecting psychological factors shaping human-bot interactions. This research addresses this gap within the context of the US-American electorate. Two datasets provide evidence that partisanship distorts (a) online users' representation of bots, (b) their ability to identify them, and (c) their intentions to interact with them. Study 1 explores global bot perceptions on through survey data from N = 452 Twitter (now X) users. Results suggest that users tend to attribute bot-related dangers to political adversaries, rather than recognizing bots as a shared threat to political discourse. Study 2 (N = 619) evaluates the consequences of such misrepresentations for the quality of online interactions. In an online experiment, participants were asked to differentiate between human and bot profiles. Results indicate that partisan leanings explained systematic judgement errors. The same data suggest that participants aim to avoid interacting with bots. However, biased judgements may undermine this motivation in praxis. In sum, the presented findings underscore the importance of interdisciplinary strategies that consider technological and human factors to address the threats posed by bots in a rapidly evolving digital landscape.

Liberal-conservative asymmetries in anti-democratic tendencies are partly explained by psychological differences in a nationally representative U.S. sample

Based on theory and research in political psychology, we hypothesized that liberal-conservative differences in right-wing authoritarianism, social dominance orientation, and political system justification would contribute to asymmetries in anti-democratic tendencies. These hypotheses were tested in a nationally representative survey of U.S. adults (N = 1557). Results revealed that conservatives were less supportive of political equality and legal rights and guarantees and more willing to defect from democratic "rules of the game" and vote for anti-democratic candidates, even after adjusting for political extremism. Mediational analyses suggested that conservatives' anti-democratic tendencies were partially attributable to higher levels of right-wing authoritarianism and social dominance orientation. Conservatives also scored higher in political system justification, which was associated with support for free speech and mitigated anti-democratic tendencies. Democrats and Republicans who approved January 6, 2021, insurrectionists were more conservative and higher in right-wing authoritarianism than those who did not. Implications for social psychology and society are discussed.

People believe political opponents accept blatant moral wrongs, fueling partisan divides

Efforts to bridge political divides often focus on navigating complex and divisive issues, but eight studies reveal that we should also focus on a more basic misperception: that political opponents are willing to accept basic moral wrongs. In the United States, Democrats, and Republicans overestimate the number of political outgroup members who approve of blatant immorality (e.g. child pornography, embezzlement). This "basic morality bias" is tied to political dehumanization and is revealed by multiple methods, including natural language analyses from a large social media corpus and a survey with a representative sample of Americans. Importantly, the basic morality bias can be corrected with a brief, scalable intervention. Providing information that just one political opponent condemns blatant wrongs increases willingness to work with political opponents and substantially decreases political dehumanization.

Attraction by pairwise coherence explains the emergence of ideological sorting

Political polarization has become a growing concern in democratic societies, as it drives tribal alignments and erodes civic deliberation among citizens. Given its prevalence across different countries, previous research has sought to understand under which conditions people tend to endorse extreme opinions. However, in polarized contexts, citizens not only adopt more extreme views but also become correlated across issues that are, a priori, seemingly unrelated. This phenomenon, known as "ideological sorting", has been receiving greater attention in recent years but the micro-level mechanisms underlying its emergence remain poorly understood. Here, we study the conditions under which a social dynamic system is expected to become ideologically sorted as a function of the mechanisms of interaction between its individuals. To this end, we developed and analyzed a multidimensional agent-based model that incorporates two mechanisms: homophily (where people tend to interact with those holding similar opinions) and pairwise-coherence favoritism (where people tend to interact with ingroups holding politically coherent opinions). We numerically integrated the model's master equations that perfectly describe the system's dynamics and found that ideological sorting only emerges in models that include pairwise-coherence favoritism. We then compared the model's outcomes with empirical data from 24,035 opinions across 67 topics and found that pairwise-coherence favoritism is significantly present in datasets that measure political attitudes but absent across topics not considered related to politics. Overall, this work combines theoretical approaches from system dynamics with model-based analyses of empirical data to uncover a potential mechanism underlying the pervasiveness of ideological sorting.

The Costs of Polarizing a Pandemic: Antecedents, Consequences, and Lessons

Polarization has been rising in the United States of America for the past few decades and now poses a significant-and growing-public-health risk. One of the signature features of the American response to the COVID-19 pandemic has been the degree to which perceptions of risk and willingness to follow public-health recommendations have been politically polarized. Although COVID-19 has proven more lethal than any war or public-health crisis in American history, the deadly consequences of the pandemic were exacerbated by polarization. We review research detailing how every phase of the COVID-19 pandemic has been polarized, including judgments of risk, spatial distancing, mask wearing, and vaccination. We describe the role of political ideology, partisan identity, leadership, misinformation, and mass communication in this public-health crisis. We then assess the overall impact of polarization on infections, illness, and mortality during the pandemic; offer a psychological analysis of key policy questions; and identify a set of future research questions for scholars and policy experts. Our analysis suggests that the catastrophic death toll in the United States was largely preventable and due, in large part, to the polarization of the pandemic. Finally, we discuss implications for public policy to help avoid the same deadly mistakes in future public-health crises.

Preregistered Replication and Extension of "Moral Hypocrisy: Social Groups and the Flexibility of Virtue"

The tendency for people to consider themselves morally good while behaving selfishly is known as moral hypocrisy. Influential work by Valdesolo and DeSteno (2007) found evidence for intergroup moral hypocrisy such that people were more forgiving of transgressions when they were committed by an in-group member than an out-group member. We conducted two experiments to examine moral hypocrisy and group membership in an online paradigm with Prolific workers from the United States: a direct replication of the original work with minimal groups (N = 610; nationally representative) and a conceptual replication with political groups (N = 606; 50% Democrats and 50% Republicans). Although the results did not replicate the original findings, we observed evidence of in-group favoritism in minimal groups and out-group derogation in political groups. The current research finds mixed evidence of intergroup moral hypocrisy and has implications for understanding the contextual dependencies of intergroup bias and partisanship.

Explaining contentious political issues promotes open-minded thinking

Cognitive scientists suggest that inviting people to explain contentious political issues might reduce intergroup toxicity because it exposes people to how poorly they understand the issue. However, whether providing explanations can result in more open-minded political thinking remains unclear. On one hand, inviting people to explain a political issue might make them more impartial and open-minded in their thinking. On the other hand, an invitation to explain a contentious political issue might lead to myside bias-rationalization of one's default position. Here, we address these contrasting predictions in five experiments (N = 1884; three pre-registered), conducted across a variety of contexts: with graduate students interacting with an actor in a laboratory setting, with US residents at the peak of the 2012 and 2016 U.S. presidential elections, with UK residents before the highly polarized 2019 Brexit vote, and with gun-control partisans. Across studies, we found that explaining politically contentious topics resulted in more open-minded thinking, an effect that generalized across coded (Studies 1-4) and self-report (Studies 3-4) measures. We also observed that participants who were made to feel like their explanations were welcomed felt closer to their discussion partner (Studies 3-4), an effect that generalized to all outgroup members with whom they disagreed with about the politically contentious issue (Study 4). We discuss the theoretical implications of these findings, and the potential for explanations to foster open-minded political engagement.

Misunderstanding the harms of online misinformation

The controversy over online misinformation and social media has opened a gap between public discourse and scientific research. Public intellectuals and journalists frequently make sweeping claims about the effects of exposure to false content online that are inconsistent with much of the current empirical evidence. Here we identify three common misperceptions: that average exposure to problematic content is high, that algorithms are largely responsible for this exposure and that social media is a primary cause of broader social problems such as polarization. In our review of behavioural science research on online misinformation, we document a pattern of low exposure to false and inflammatory content that is concentrated among a narrow fringe with strong motivations to seek out such information. In response, we recommend holding platforms accountable for facilitating exposure to false and extreme content in the tails of the distribution, where consumption is highest and the risk of real-world harm is greatest. We also call for increased platform transparency, including collaborations with outside researchers, to better evaluate the effects of online misinformation and the most effective responses to it. Taking these steps is especially important outside the USA and Western Europe, where research and data are scant and harms may be more severe.

Beneficial effects of communicating intentions when delivering moral criticism: Cognitive and neural responses

People often do not accept criticism on their morality, especially when delivered by outgroup members. In two preregistered studies, we investigated whether people become more receptive to such negative feedback when feedback senders communicate their intention to help. Participants received negative feedback from ostensible others on their selfish (rather than altruistic) decisions in a donation task. We manipulated the identity of a feedback sender (ingroup vs. outgroup) and the intention that they provided for giving feedback. A sender either did not communicate any intentions, indicated the intention to help the feedback receiver improve, or communicated the intention to show moral superiority. We measured participants' self-reported responses to the feedback (Study 1, N = 44) and additionally recorded an EEG in Study 2 (N = 34). Results showed that when no intentions were communicated, participants assumed worse intentions from outgroup senders than ingroup senders (Study 1). However, group membership had no significant effect once feedback senders made their intentions explicit. Moreover, across studies, when feedback senders communicated their intention to help, participants perceived feedback as less unfair compared with when senders tried to convey their moral superiority. Complementing these results, exploratory event-related potential results of Study 2 suggested that communicating the intention to help reduced participants' attentional vigilance toward negative feedback messages on their morality (i.e., decreased P200 amplitudes). These results demonstrate the beneficial effects of communicating the intention to help when one tries to encourage others' moral growth through criticism.

The affective gap: a call for a comprehensive examination of the discrete emotions underlying affective polarization

Bakker and Lelkes (2024) point at a critical gap in research on affective polarisation: the limited understanding of its affective components, mainly due to the reliance on a unidimensional operationalisation of affect in affective polarisation. They advocate for a broader approach to study affect, integrating explicit and implicit measures, and call on emotion specialists to address this gap. Acknowledging the complexity of affect in the ideological divide, we argue that the lack of a thorough examination of the distinct role of discrete emotions constitutes the primary "affective gap". Drawing from studies on the relationship between ideological groups and utilising a discrete emotions approach, we contest the prevailing assumption that hatred predominantly underlies affective polarisation. Instead, we propose that disappointment, better captures the intricate dynamics between ideological groups. We argue that such nuanced approach, regarding the affective component of affective polarisation enhances our understanding of the phenomenon and shed light on its implications for societies.

Zero-sum beliefs and the avoidance of political conversations

Although researchers have argued that exposure to diverse views may help reduce political divisions in society, people often avoid discussing politics with ideologically opposed others. We investigate the avoidance of political conversations surrounding highly contested elections in Israel and the U.S. Specifically, we examine the relationship between people's belief that politics is a zero-sum game and their tendency to avoid talking about politics with ideologically opposed others. In two studies conducted in the days leading up to their countries' elections, we found that Israeli and American voters who view politics as zero-sum avoided political discussions with ideologically opposed others. Furthermore, zero-sum beliefs about politics statistically predicted the avoidance of political conversations through two distinct mechanisms: perceived conflict and a lack of receptiveness to opposing views. Finally, in a longitudinal design, we found that zero-sum beliefs about politics statistically and robustly predicted the avoidance of political conversation one week later.

Blocking of counter-partisan accounts drives political assortment on Twitter

There is strong political assortment of Americans on social media networks. This is typically attributed to preferential tie formation (i.e. homophily) among those with shared partisanship. Here, we demonstrate an additional factor beyond homophily driving assorted networks: preferential prevention of social ties. In two field experiments on Twitter, we created human-looking bot accounts that identified as Democrats or Republicans, and then randomly assigned users to be followed by one of these accounts. In addition to preferentially following-back copartisans, we found that users were 12 times more likely to block counter-partisan accounts compared to copartisan accounts in the first experiment, and 4 times more likely to block counter-partisan accounts relative to a neutral account or a copartisan account in the second experiment. We then replicated these findings in a survey experiment and found evidence of a key motivation for blocking: wanting to avoid seeing any content posted by the blocked user. Additionally, we found that Democrats preferentially blocked counter-partisans more than Republicans, and that this asymmetry was likely due to blocking accounts who post low-quality or politically slanted content (rather than an asymmetry in identity-based blocking). Our results demonstrate that preferential blocking of counter-partisans is an important phenomenon driving political assortment on social media.

Managing emotions in the age of political polarization: A randomized controlled trial comparing mindfulness to cognitive reappraisal

Emotional appraisals of political stimuli (e.g., videos) have been shown to drive shared neural encoding, which correspond to shared, yet divisive, interpretations of such stimuli. However, mindfulness practice may entrain a form of emotion regulation that de-automatizes social biases, possibly through alteration of such neural mechanisms. The present study combined a naturalistic neuroimaging paradigm and a randomized controlled trial to examine the effects of short-term mindfulness training (MT) (n = 35) vs structurally equivalent Cognitive Reappraisal training (CT) (n = 37) on politically-situated emotions while evaluating the mechanistic role of prefrontal cortical neural synchrony. Participants underwent functional near-infrared spectroscopy (fNIRS) recording while viewing inflammatory partisan news clips and continuously rating their momentary discrete emotions. MT participants were more likely to respond with extreme levels of anger (odds ratio = 0.12, p < .001) and disgust (odds ratio = 0.08, p < .001) relative to CT participants. Neural synchrony-based analyses suggested that participants with extreme emotion reactions exhibited greater prefrontal cortical neural synchrony, but that this pattern was less prominent in participants receiving MT relative to CT (CT > MT; channel 1 ISC = .040, p = .030).

Misplaced Divides? Discussing Political Disagreement With Strangers Can Be Unexpectedly Positive

Differences of opinion between people are common in everyday life, but discussing those differences openly in conversation may be unnecessarily rare. We report three experiments (N = 1,264 U.S.-based adults) demonstrating that people's interest in discussing important but potentially divisive topics is guided by their expectations about how positively the conversation will unfold, leaving them more interested in having a conversation with someone who agrees versus disagrees with them. People's expectations about their conversations, however, were systematically miscalibrated such that people underestimated how positive these conversations would be-especially in cases of disagreement. Miscalibrated expectations stemmed from underestimating the degree of common ground that would emerge in conversation and from failing to appreciate the power of social forces in conversation that create social connection. Misunderstanding the outcomes of conversation could lead people to avoid discussing disagreements more often, creating a misplaced barrier to learning, social connection, free inquiry, and free expression.

Uncommon and nonpartisan: Antidemocratic attitudes in the American public

Democratic regimes flourish only when there is broad acceptance of an extensive set of norms and values. In the United States, fundamental democratic norms have recently come under threat from prominent Republican officials. We investigate whether this antidemocratic posture has spread from the elite level to rank-and-file partisans. Exploiting data from a massive repeated cross-sectional and panel survey ([Formula: see text] = 45,095 and 5,231 respectively), we find that overwhelming majorities of the public oppose violations of democratic norms, and virtually nobody supports partisan violence. This bipartisan consensus remains unchanged over time despite high levels of affective polarization and exposure to divisive elite rhetoric during the 2022 political campaign. Additionally, we find no evidence that elected officials' practice of election denialism encourages their constituents to express antidemocratic attitudes. Overall, these results suggest that the clear and present threat to American democracy comes from unilateral actions by political elites that stand in contrast to the views of their constituents. In closing, we consider the implications of the stark disconnect between the behavior of Republican elites and the attitudes of Republican voters.

The acceptance of evolution: A developmental view of Generation X in the United States

The public acceptance of evolution remains a contentious issue in the United States. Numerous investigations have used national cross-sectional studies to examine the factors associated with the acceptance or rejection of evolution. This analysis uses a 33-year longitudinal study that followed the same 5000 public-school students from grade 7 through midlife (ages 45-48) and is the first to do so in regard to evolution. A set of structural equation models demonstrate the complexity and changing nature of influences over these three decades. Parents and local influences are strong during the high school years. The combination of post-secondary education and occupational and family choices demonstrate that the 15 years after high school are the switchyards of life.

Beyond Trolleyology: The CNI Model of Moral-Dilemma Responses

PUBLIC ABSTRACT

How do people make judgments about actions that violate moral norms yet maximize the greater good (e.g., sacrificing the well-being of a small number of people for the well-being of a larger number of people)? Research on this question has been criticized for relying on highly artificial scenarios and for conflating multiple distinct factors underlying responses in moral dilemmas. The current article reviews research that used a computational modeling approach to disentangle the roles of multiple distinct factors in responses to plausible moral dilemmas based on real-world events. By disentangling sensitivity to consequences, sensitivity to moral norms, and general preference for inaction versus action in responses to realistic dilemmas, the reviewed work provides a more nuanced understanding of how people make judgments about the right course of action in moral dilemmas.

The Misleading count: an identity-based intervention to counter partisan misinformation sharing

Interventions to counter misinformation are often less effective for polarizing content on social media platforms. We sought to overcome this limitation by testing an identity-based intervention, which aims to promote accuracy by incorporating normative cues directly into the social media user interface. Across three pre-registered experiments in the US (N = 1709) and UK (N = 804), we found that crowdsourcing accuracy judgements by adding a Misleading count (next to the Like count) reduced participants' reported likelihood to share inaccurate information about partisan issues by 25% (compared with a control condition). The Misleading count was also more effective when it reflected in-group norms (from fellow Democrats/Republicans) compared with the norms of general users, though this effect was absent in a less politically polarized context (UK). Moreover, the normative intervention was roughly five times as effective as another popular misinformation intervention (i.e. the accuracy nudge reduced sharing misinformation by 5%). Extreme partisanship did not undermine the effectiveness of the intervention. Our results suggest that identity-based interventions based on the science of social norms can be more effective than identity-neutral alternatives to counter partisan misinformation in politically polarized contexts (e.g. the US). This article is part of the theme issue 'Social norm change: drivers and consequences'.

Twitter (X) use predicts substantial changes in well-being, polarization, sense of belonging, and outrage

In public debate, Twitter (now X) is often said to cause detrimental effects on users and society. Here we address this research question by querying 252 participants from a representative sample of U.S. Twitter users 5 times per day over 7 days (6,218 observations). Results revealed that Twitter use is related to decreases in well-being, and increases in political polarization, outrage, and sense of belonging over the course of the following 30 minutes. Effect sizes were comparable to the effect of social interactions on well-being. These effects remained consistent even when accounting for demographic and personality traits. Different inferred uses of Twitter were linked to different outcomes: passive usage was associated with lower well-being, social usage with a higher sense of belonging, and information-seeking usage with increased outrage and most effects were driven by within-person changes.

The unequal landscape of civic opportunity in America

The hollowing of civil society has threatened effective implementation of scientific solutions to pressing public challenges-which often depend on cultivating pro-social orientations commonly studied under the broad umbrella of social capital. Although robust research has studied the constituent components of social capital from the demand side (that is, the orientations people need for collective life in pluralistic societies, such as trust, cohesion and connectedness), the same precision has not been brought to the supply side. Here we define the concept of civic opportunity-opportunities people have to encounter civic experiences necessary for developing such orientations-and harness data science to map it across America. We demonstrate that civic opportunity is more highly correlated with pro-social outcomes such as mutual aid than other measures, but is unequally distributed, and its sources are underrepresented in the public dialogue. Our findings suggest greater attention to this fundamentally uneven landscape of civic opportunity.

Academics are more specific, and practitioners more sensitive, in forecasting interventions to strengthen democratic attitudes

Concern over democratic erosion has led to a proliferation of proposed interventions to strengthen democratic attitudes in the United States. Resource constraints, however, prevent implementing all proposed interventions. One approach to identify promising interventions entails leveraging domain experts, who have knowledge regarding a given field, to forecast the effectiveness of candidate interventions. We recruit experts who develop general knowledge about a social problem (academics), experts who directly intervene on the problem (practitioners), and nonexperts from the public to forecast the effectiveness of interventions to reduce partisan animosity, support for undemocratic practices, and support for partisan violence. Comparing 14,076 forecasts submitted by 1,181 forecasters against the results of a megaexperiment (n = 32,059) that tested 75 hypothesized effects of interventions, we find that both types of experts outperformed members of the public, though experts differed in how they were accurate. While academics' predictions were more specific (i.e., they identified a larger proportion of ineffective interventions and had fewer false-positive forecasts), practitioners' predictions were more sensitive (i.e., they identified a larger proportion of effective interventions and had fewer false-negative forecasts). Consistent with this, practitioners were better at predicting best-performing interventions, while academics were superior in predicting which interventions performed worst. Our paper highlights the importance of differentiating types of experts and types of accuracy. We conclude by discussing factors that affect whether sensitive or specific forecasters are preferable, such as the relative cost of false positives and negatives and the expected rate of intervention success.

Partisan styles of self-presentation in U.S. Twitter bios

Political polarization in the United States goes beyond divided opinions on key political issues, extending to realms of culture, lifestyle, and social identity once thought to be apolitical. Using a sample of 1 million Twitter bios, this study investigates how users' partisan self-presentation on social media tends to include cultural as well as political markers. Representing the text in Twitter bios as semantic networks, the study reveals clear partisan differences in how users describe themselves, even on topics that seem apolitical. Consequently, active Twitter users' political alignments can be statistically inferred from the non-political references in their bios, even in the absence of explicitly partisan language. These findings offer further evidence of partisan polarization that is aligned with lifestyle preferences. Further research is needed to determine if users are aware of that alignment, which might indicate the politicization of lifestyle preferences. The findings also suggest an under-recognized way social media can promote polarization, not through political discourse or argument, but simply in how users present cultural and lifestyle preferences on those platforms.

Partisan animosity through the lens of blame: Partisan animosity can be reduced by a historicist thinking intervention

Partisan animosity has been on the rise in America. Partisan animosity involves blame, wherein political partisans blame outparty members for their beliefs and actions. Here, we examine whether a historicist thinking intervention-drawn from research on blame mitigation-can reduce partisan animosity. The intervention consisted of three components: (1) a narrative about the idiosyncratic development of one political opponent paired with (2) a message about how unique life experiences shape everyone's political beliefs and (3) a suggestion that outparty members can be changed by future formative experiences. Experiments 1 and 2 showed that the intervention reduced cold feelings-measured via Feeling Thermometer-towards the outparty for both Democrats and Republicans. Experiments 3 and 4 focused on more specific emotional changes. Experiment 3 showed that, for Democrats, the intervention increased compassion. Experiment 4 showed that, for Republicans, the intervention reduced disgust, disapproval, anger, and contempt, but had no impact on compassion. For Democrats, but not for Republicans, reductions in animosity were mediated by reduced perceptions of control of self-formation, the mediator identified in prior work on historicist thinking and blame mitigation.

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.

Respondents with more extreme views show moderation of opinions in multi-year surveys in the USA and the Netherlands

People with extreme political attitudes are often assumed to be more resistant to change than moderates. If this assumption is true, extreme attitudes would ossify and continuously aggravate intergroup conflict and polarization. To test this assumption of stubborn extremists, we use large-scale panel surveys of attitudes towards policy issues and general ideologies across up to 13 years (combined N = 16,238). By tracking the same people across multi-year periods, we are able to ascertain whether extreme attitude holders exhibit less change in policy attitudes than moderates. The results revealed that extreme attitude holders are more likely to change their attitudes than moderates across various policy issues and general ideologies, and tend to directionally moderate over time. A final experiment finds that lay people incorrectly believe that extreme attitudes holders are more resistant to change, contrary to the results found here. We discuss the implications of this finding for understanding the evolution of extreme attitude holders, the misperception of ideological and policy differences, and the role of inaccurate out-group perceptions in shaping polarization and intergroup conflict.

Meta-perception and misinformation

Research on political misperceptions is flourishing across disciplines. Literature on misinformation susceptibility and political group meta-perceptions have arisen independently, both seeking to understand how inaccurate social beliefs of the first and second order respectively contribute to political polarization. Here we review these literatures and argue for greater integration. We highlight four domains where these two literatures intersect: how inaccurate group meta-perceptions may increase misinformation susceptibility, how misinformation may itself convey inaccurate second-order information, how second-order perceptions of misinformation belief may increase misinformation susceptibility, and how reputational concerns may affect misinformation engagement. Our hope is to illuminate fruitful avenues of future research and inspire scholars of political misperceptions to pursue unified theoretical models of how misperceptions drive negative political outcomes.

Listening to bridge societal divides

The U.S. is plagued by a variety of societal divides across political orientation, race, and gender, among others. Listening has the potential to be a key element in spanning these divides. Moreover, the benefits of listening for mitigating social division has become a culturally popular idea and practice. Recent evidence suggests that listening can bridge divides in at least two ways: by improving outgroup sentiment and by granting outgroup members greater status and respect. When reviewing this literature, we pay particular attention to mechanisms and to boundary conditions, as well as to the possibility that listening can backfire. We also review a variety of current interventions designed to encourage and improve listening at all levels of the culture cycle. The combination of recent evidence and the growing popular belief in the significance of listening heralds a bright future for research on the many ways that listening can diffuse stereotypes and improve attitudes underlying intergroup division.

Reputations for treatment of outgroup members can prevent the emergence of political segregation in cooperative networks

Reputation systems promote cooperation and tie formation in social networks. But how reputations affect cooperation and the evolution of networks is less clear when societies are characterized by fundamental, identity-based, social divisions like those centered on politics in the contemporary U.S. Using a large web-based experiment with participants (N = 1073) embedded in networks where each tie represents the opportunity to play a dyadic iterated prisoners' dilemma, we investigate how cooperation and network segregation varies with whether and how reputation systems track behavior toward members of the opposing political party (outgroup members). As predicted, when participants know others' political affiliation, early cooperation patterns show ingroup favoritism. As a result, networks become segregated based on politics. However, such ingroup favoritism and network-level political segregation is reduced in conditions in which participants know how others behave towards participants from both their own party and participants from the other party. These findings have implications for our understanding of reputation systems in polarized contexts.

Leveraging AI for democratic discourse: Chat interventions can improve online political conversations at scale

Political discourse is the soul of democracy, but misunderstanding and conflict can fester in divisive conversations. The widespread shift to online discourse exacerbates many of these problems and corrodes the capacity of diverse societies to cooperate in solving social problems. Scholars and civil society groups promote interventions that make conversations less divisive or more productive, but scaling these efforts to online discourse is challenging. We conduct a large-scale experiment that demonstrates how online conversations about divisive topics can be improved with AI tools. Specifically, we employ a large language model to make real-time, evidence-based recommendations intended to improve participants' perception of feeling understood. These interventions improve reported conversation quality, promote democratic reciprocity, and improve the tone, without systematically changing the content of the conversation or moving people's policy attitudes.

They Saw a Hearing: Democrats' and Republicans' Perceptions of and Responses to the Ford-Kavanaugh Hearings

In several highly publicized hearings, Dr. Christine Blasey Ford and Judge Brett Kavanaugh presented two opposing accounts of an alleged sexual assault. In the wake of these proceedings, partisans appeared similarly divided in how they regarded this political event. Using a U.S. national sample (N = 2,474) and a mixed-methods design, we investigated partisans' perceptions of, and responses to, the Ford-Kavanaugh hearings. Respondents reported their views of the hearings soon after they occurred. We used topic modeling to analyze these open-ended responses and found uniquely partisan topics emerged, including judicial impartiality and due process. Acute stress (AS) responses to the hearings were also related to partisan identities and perceptions; both Republicans (incidence rate ratio [IRR] = 0.81, 95% confidence interval [CI] = [0.78, 0.84]) and individuals who wrote more about Republican topics (IRR = 0.72, 95% CI = [0.56, 0.92]) reported lower AS than their Democratic counterparts. Results demonstrate different partisan perceptions with implications for mental health outcomes.

The social media discourse of engaged partisans is toxic even when politics are irrelevant

Prevailing theories of partisan incivility on social media suggest that it derives from disagreement about political issues or from status competition between groups. This study-which analyzes the commenting behavior of Reddit users across diverse cultural contexts (subreddits)-tests the alternative hypothesis that such incivility derives in large part from a selection effect: Toxic people are especially likely to opt into discourse in partisan contexts. First, we examined commenting behavior across over 9,000 unique cultural contexts (subreddits) and confirmed that discourse is indeed more toxic in partisan (e.g. r/progressive, r/conservatives) than in nonpartisan contexts (e.g. r/movies, r/programming). Next, we analyzed hundreds of millions of comments from over 6.3 million users and found robust evidence that: (i) the discourse of people whose behavior is especially toxic in partisan contexts is also especially toxic in nonpartisan contexts (i.e. people are not politics-only toxicity specialists); and (ii) when considering only nonpartisan contexts, the discourse of people who also comment in partisan contexts is more toxic than the discourse of people who do not. These effects were not driven by socialization processes whereby people overgeneralized toxic behavioral norms they had learned in partisan contexts. In contrast to speculation about the need for partisans to engage beyond their echo chambers, toxicity in nonpartisan contexts was higher among people who also comment in both left-wing and right-wing contexts (bilaterally engaged users) than among people who also comment in only left-wing or right-wing contexts (unilaterally engaged users). The discussion considers implications for democratic functioning and theories of polarization.

Social Psychological Perspectives on Political Polarization: Insights and Implications for Climate Change

Political polarization is a barrier to enacting policy solutions to global issues. Social psychology has a rich history of studying polarization, and there is an important opportunity to define and refine its contributions to the present political realities. We do so in the context of one of the most pressing modern issues: climate change. We synthesize the literature on political polarization and its applications to climate change, and we propose lines of further research and intervention design. We focus on polarization in the United States, examining other countries when literature was available. The polarization literature emphasizes two types of mechanisms of political polarization: (1) individual-level psychological processes related to political ideology and (2) group-level psychological processes related to partisan identification. Interventions that address group-level processes can be more effective than those that address individual-level processes. Accordingly, we emphasize the promise of interventions leveraging superordinate identities, correcting misperceived norms, and having trusted leaders communicate about climate change. Behavioral interventions like these that are grounded in scientific research are one of our most promising tools to achieve the behavioral wedge that we need to address climate change and to make progress on other policy issues.

Empathic Conservatives and Moralizing Liberals: Political Intergroup Empathy Varies by Political Ideology and Is Explained by Moral Judgment

Empathy has the potential to bridge political divides. Here, we examine barriers to cross-party empathy and explore when and why these differ for liberals and conservatives. In four studies, U.S. and U.K. participants (total N = 4,737) read hypothetical scenarios and extended less empathy to suffering political opponents than allies or neutral targets. These effects were strongly shown by liberals but were weaker among conservatives, such that conservatives consistently showed more empathy to liberals than liberals showed to conservatives. This asymmetry was partly explained by liberals' harsher moral judgments of outgroup members (Studies 1-4) and the fact that liberals saw conservatives as more harmful than conservatives saw liberals (Studies 3 and 4). The asymmetry persisted across changes in the U.S. government and was not explained by perceptions of political power (Studies 3 and 4). Implications and future directions are discussed.

Partisan self-identification predicts attitudes of South Dakota nurses toward COVID-19 vaccine mandate for healthcare workers

Objectives

Nurses are at greater risk of infection from COVID-19. However, mistrust of the vaccine exists even among this group. In the United States, the government implemented a vaccine mandate for health care workers to increase vaccination rates. This study investigated the drivers of nurses' attitudes toward the mandate.

Methods

We fielded a survey to study the attitudes of nurses toward COVID-19 vaccine mandate for HCWs. We contacted nurses in South Dakota, United States, based on the information from the South Dakota Board of Nursing. The survey was open in June and July 2022. We conducted a multivariate regression analysis to identify the factors that predict attitudes toward this regulation.

Results

We received 1,084 responses. Results of regression analysis showed statistically significant relationships between partisan self-identification, evangelical identity, gender, and COVID-19 vaccination status and support for COVID-19 vaccine mandate for healthcare workers. Age, time with patients, positive COIVD-19 test in the last year, education, and nurse classification variables were not statistically significant.

Conclusions

The same factors that drive people's attitudes toward COVID-19 mitigation policies also explain nurses' attitudes toward a vaccine mandate for healthcare workers. The politicization of the COVID-19 pandemic is present also among nurses. Health care officials should be mindful of the influence of these biases as they evaluate the vaccine mandate and develop new regulations.

Reducing political polarization in the United States with a mobile chat platform

Do anonymous online conversations between people with different political views exacerbate or mitigate partisan polarization? We created a mobile chat platform to study the impact of such discussions. Our study recruited Republicans and Democrats in the United States to complete a survey about their political views. We later randomized them into treatment conditions where they were offered financial incentives to use our platform to discuss a contentious policy issue with an opposing partisan. We found that people who engage in anonymous cross-party conversations about political topics exhibit substantial decreases in polarization compared with a placebo group that wrote an essay using the same conversation prompts. Moreover, these depolarizing effects were correlated with the civility of dialogue between study participants. Our findings demonstrate the potential for well-designed social media platforms to mitigate political polarization and underscore the need for a flexible platform for scientific research on social media.

The attitudinal space framework: Embracing the multidimensionality of attitudinal diversity

Attitude polarization describes an increasing attitude difference between groups and is increasingly recognized as a multidimensional phenomenon. However, a unified framework to study polarization across multiple dimensions is lacking. We introduce the attitudinal space framework (ASF) to fully quantify attitudinal diversity. We highlight two key measures-attitudinal extremization and attitudinal dispersion-to quantify across- and within-group attitudinal patterns. First, we show that affective polarization in the US electorate is weaker than previously thought based on mean differences alone: in both Democrat and Republican partisans, attitudinal dispersion increased between 1988 and 2008. Second, we examined attitudes toward wolves in Germany. Despite attitude differences between regions with and without wolves, we did not find differences in attitudinal extremization or dispersion, suggesting only weak attitude polarization. These results illustrate how the ASF is applicable to a wide range of social systems and offers an important avenue to understanding societal transformations.

Why voters who value democracy participate in democratic backsliding

Around the world, citizens are voting away the democracies they claim to cherish. Here we present evidence that this behaviour is driven in part by the belief that their opponents will undermine democracy first. In an observational study (N = 1,973), we find that US partisans are willing to subvert democratic norms to the extent that they believe opposing partisans are willing to do the same. In experimental studies (N = 2,543, N = 1,848), we revealed to partisans that their opponents are more committed to democratic norms than they think. As a result, the partisans became more committed to upholding democratic norms themselves and less willing to vote for candidates who break these norms. These findings suggest that aspiring autocrats may instigate democratic backsliding by accusing their opponents of subverting democracy and that we can foster democratic stability by informing partisans about the other side's commitment to democracy.

COVID-19 and social media: Beyond polarization

The COVID-19 pandemic brought upon a massive wave of disinformation, exacerbating polarization in the increasingly divided landscape of online discourse. In this context, popular social media users play a major role, as they have the ability to broadcast messages to large audiences and influence public opinion. In this article, we make use of openly available data to study the behavior of popular users discussing the pandemic on Twitter. We tackle the issue from a network perspective, considering users as nodes and following relationships as directed edges. The resulting network structure is modeled by embedding the actors in a latent social space, where users closer to one another have a higher probability of following each other. The results suggest the existence of two distinct communities, which can be interpreted as "generally pro" and "generally against" vaccine mandates, corroborating existing evidence on the pervasiveness of echo chambers on the platform. By focusing on a number of notable users, such as politicians, activists, and news outlets, we further show that the two groups are not entirely homogeneous, and that not just the two poles are represented. To the contrary, the latent space captures an entire spectrum of beliefs between the two extremes, demonstrating that polarization, while present, is not the only driver of the network, and that more moderate, "central" users are key players in the discussion.

Like-minded sources on Facebook are prevalent but not polarizing

Many critics raise concerns about the prevalence of 'echo chambers' on social media and their potential role in increasing political polarization. However, the lack of available data and the challenges of conducting large-scale field experiments have made it difficult to assess the scope of the problem1,2. Here we present data from 2020 for the entire population of active adult Facebook users in the USA showing that content from 'like-minded' sources constitutes the majority of what people see on the platform, although political information and news represent only a small fraction of these exposures. To evaluate a potential response to concerns about the effects of echo chambers, we conducted a multi-wave field experiment on Facebook among 23,377 users for whom we reduced exposure to content from like-minded sources during the 2020 US presidential election by about one-third. We found that the intervention increased their exposure to content from cross-cutting sources and decreased exposure to uncivil language, but had no measurable effects on eight preregistered attitudinal measures such as affective polarization, ideological extremity, candidate evaluations and belief in false claims. These precisely estimated results suggest that although exposure to content from like-minded sources on social media is common, reducing its prevalence during the 2020 US presidential election did not correspondingly reduce polarization in beliefs or attitudes.

Political (Meta-)Dehumanization in Mental Representations: Divergent Emphases in the Minds of Liberals Versus Conservatives

We conducted two reverse-correlation studies, as well as two pilot studies reported in the online supplement (total N = 1,411), on the topics of (a) whether liberals and conservatives differ in the types of dehumanization that they cognitively emphasize when mentally representing one another, and if so, (b) whether liberals and conservatives are sensitive to how they are represented in the minds of political outgroup members. Results suggest that partisans indeed differ in the types of dehumanization that they cognitively emphasize when mentally representing one another: whereas conservatives' dehumanization of liberals emphasizes immaturity (vs. savagery), liberals' dehumanization of conservatives more strongly emphasizes savagery (vs. immaturity). In addition, results suggest that partisans may be sensitive to how they are represented. That is, partisans' meta-representations-their representations of how the outgroup represents the ingroup-appear to accurately index the relative emphases of these two dimensions in the minds of political outgroup members.

Mental health symptoms following the January 6th attack on the United States Capitol

On January 6, 2021, rioters stormed the US Capitol to overturn the Congressional certification of Joseph Biden as the 46th president of the United States. In previous work, the symbolic dis/empowerment framework, as a result of sociopolitical context, has influenced health outcomes in certain sub-populations. We examine whether the Capitol Riot corresponds with an increase in mental health symptoms and explore whether this relation differs by individual political party affiliation and/or state electoral college victory. We utilize the Understanding America Study, a nationally representative panel of adults, between March 10, 2020-July 11, 2021. Using fixed effects linear regression, we find a modest increase above expected levels in mental health symptoms immediately following the Capitol Riot. This result holds for Democrats overall, Democrats in Biden states, and when restricting analyses to only states that voted for Biden (or separately, for Trump). Democrats show the greatest increase of mental health symptoms following the Capital Riot, supporting the symbolic dis/empowerment framework as well as notions of political polarization and allegiance. Social and political events of national importance may adversely affect mental health of specific subpopulations.

Individual-Community Misalignment in Partisan Identity Predicts Distancing From Norms During the COVID-19 Pandemic

This study investigated whether misalignment between an individual and their community in partisan identity predicted psychological and behavioral distancing from local COVID-19 norms. A nationally representative sample of Republicans and Democrats provided longitudinal data in April (N = 3,492) and June 2020 (N = 2,649). Democrats in Republican communities reported especially heightened better-than-average estimates, perceiving themselves as more adherent to and approving of non-pharmaceutical interventions (NPI; e.g., mask wearing) than their community. Democrats'better-than-average estimates reflected high approval and behavior in Republican communities and substantial norm underestimation. Republicans in Democratic communities did not evidence worse-than-average estimates. In longitudinal models, injunctive norms only predicted NPI behavior when individual and community partisan identity were aligned. The strong personal approval-behavior association did not depend on misalignment; there were no effects of descriptive norms. Normative messages may have limited efficacy for a sizable subpopulation in politically polarized contexts, such as the COVID-19 pandemic.