Fear and Loathing across Party Lines: New Evidence on Group Polarization

Iyengar, Shanto; Westwood, Sean J.

doi:10.1111/ajps.12152

Cited by 1,333 publications

(1,048 citation statements)

References 51 publications

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“…The giver is instructed to divide the resource between himself or herself and the receiver in any way s/he chooses. The dictator game has been used with increasing frequency to examine intergroup biases (e.g., Bendersky, 2014;Rand, Pfeiffer, Dreber, Sheketoff, Wernerfelt, & Benkler, 2009), and has been described as offering the opportunity to assess "pure" group dislike and prejudice (Fershtman & Gneezy, 2001;Iyengar & Westwood, 2014).…”

Section: Studymentioning

confidence: 99%

Social and economic ideologies differentially predict prejudice across the political spectrum, but social issues are most divisive.

Crawford

Brandt

Inbar

et al. 2017

Journal of Personality and Social Psychology

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Liberals and conservatives both express prejudice toward ideologically dissimilar others . Previous work on ideological prejudice did not take advantage of evidence showing that ideology is multi-dimensional, with social and economic ideologies representing related but separable belief systems. In five studies (total N = 4912), we test three competing hypotheses of a multi-dimensional account of ideological prejudice. The dimension-specific symmetry hypothesis predicts that social and economic ideologies differentially predict prejudice against targets who are perceived to vary on the social and economic political dimensions, respectively.The social primacy hypothesis predicts that such ideological worldview conflict is experienced more strongly along the social than economic dimension. The social-specific asymmetry hypothesis predicts that social conservatives will be more prejudiced than social liberals, with no specific hypotheses for the economic dimension. Using multiple target groups, multiple prejudice measures (e.g., global evaluations, behavior), and multiple social and economic ideology measures (self-placement, issue positions), we found relatively consistent support for the dimension-specific symmetry and social primacy hypotheses, and no support for the socialspecific asymmetry hypothesis. These results suggest that worldview conflict and negative intergroup attitudes and behaviors are dimension-specific, but that the social dimension appears to inspire more political conflict than the economic dimension.

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Section: Studymentioning

confidence: 99%

Social and economic ideologies differentially predict prejudice across the political spectrum, but social issues are most divisive.

Crawford

Brandt

Inbar

et al. 2017

Journal of Personality and Social Psychology

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show abstract

“…However, against a backdrop of intense affective polarization (Clifford, 2017;Huddy, Mason, & Aaroe, 2015;Iyengar, Sood, & Lelkes, 2012;Iyengar & Westwood, 2015), the mismatch hypothesis predicts that moral attitudes will play an important role in modelling how people explain the actions of allies and rivals. For example, agent-focused attributions should seem less appropriate when explaining why someone defected for the rival party, despite the high diagnostic value of that action.…”

Section: Study 5: Partisan Attributionmentioning

confidence: 99%

When do circumstances excuse? Moral prejudices and beliefs about the true self drive preferences for agency-minimizing explanations

Cullen

2018

Cognition

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A B S T R A C TWhen explaining human actions, people usually focus on a small subset of potential causes. What leads us to prefer certain explanations for valenced actions over others? The present studies indicate that our moral attitudes often predict our explanatory preferences far better than our beliefs about how causally sensitive actions are to features of the actor's environment. Study 1 found that high-prejudice participants were much more likely to endorse nonagential explanations of an erotic same-sex encounter, such as that one of the men endured a stressful event earlier that day. Study 2 manipulated participants' beliefs about how the agent's behavior depended on features of his environment, finding that such beliefs played no clear role in modeling participants' explanatory preferences. This result emerged both with low-and high-prejudice, US and Indian participants, suggesting that these findings probably reflect a species-typical feature of human psychology. Study 3 found that moral attitudes also predicted explanations for a woman's decision to abort her pregnancy (3a) and a person's decision to convert to Islam (3b). Study 4 found that luck in an action's etiology tends to undermine perceptions of blame more readily than perceptions of praise. Finally, Study 5 found that when explaining support for a rival ideology, both Liberals and Conservatives downplay agential causes while emphasizing environmental ones. Taken together, these studies indicate that our explanatory preferences often reflect a powerful tendency to represent agents as possessing virtuous true selves. Consequently, situation-focused explanations often appear salient because people resist attributing negatively valenced actions to the true self. There is a person/situation distinction, but it is normative.

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“…The code below was used to calculate CACE for the three different levels of compliance described above: , data = data) #calculate cluster robust standard errors data$bin_maker<-as.numeric(data$bin_maker) output<-cluster.robust.se(results, data$bin_maker) [2,] return(output)} #run models full_compliance_models <-lapply(datasets, function(x) CACE_fc(x)) half_compliance_models <-lapply(datasets, function(x) CACE_hc(x)) bot_follower_models <-lapply(datasets, function(x) CACE_bf(x)) #extract results for republicans republican_full_compliance_cace<-as.data.frame(t(full_compliance_models[ [2]])) republican_full_compliance_cace$sample<-"republicans_full_compliance" republican_full_compliance_cace$party<-"republicans" names(republican_full_compliance_cace)< -c("estimate","se","t","p","sample","party") republican_half_compliance_cace<-as.data.frame(t(half_compliance_models[ [2]])) republican_half_compliance_cace$sample<-"republicans_half_compliance" republican_half_compliance_cace$party<-"republicans" names(republican_half_compliance_cace)<-c("estimate","se","t","p","sample","party") republican_bot_follower_cace<-as.data.frame(t(bot_follower_models[ [2]])) republican_bot_follower_cace$sample<-"republicans_bot_follower" republican_bot_follower_cace$party<-"republicans" names(republican_bot_follower_cace)<-c("estimate","se","t","p","sample","party") #extract results for democrats democrat_full_compliance_cace<-data.frame(t(full_compliance_models[ [1]])) democrat_full_compliance_cace$sample<-"democrats_full_compliance" democrat_full_compliance_cace$party<-"democrats" names(democrat_full_compliance_cace)<-c("estimate","se","t","p","sample","party") democrat_half_compliance_cace<-as.data.frame(t(half_compliance_models[ [1]])) democrat_half_compliance_cace$sample<-"democrats_half_compliance" democrat_half_compliance_cace$party<-"democrats" names(democrat_half_compliance_cace)<-c("estimate","se","t","p","sample","party") democrat_bot_follower_cace<-as.data.frame(t(bot_follower_models[ [1]])) democrat_bot_follower_cace$sample<-"democrats_bot_follower" democrat_bot_follower_cace$party<-"democrats" names(democrat_bot_follower_cace)<-c("estimate","se","t","p","sample","party")…”

Section: Complier Average Causal Effectsmentioning

confidence: 99%

Exposure to Opposing Views can Increase Political Polarization: Evidence from a Large-Scale Field Experiment on Social Media

Bail¹,

Argyle²,

Brown³

et al. 2018

Preprint

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There is mounting concern that social media sites contribute to political polarization by creating "echo chambers" that insulate people from opposing views about current events. We surveyed a large sample of Democrats and Republicans who visit Twitter at least three times each week about a range of social policy issues. One week later, we randomly assigned respondents to a treatment condition in which they were offered financial incentives to follow a 1 Twitter bot for one month that exposed them to messages produced by elected officials, organizations, and other opinion leaders with opposing political ideologies. Respondents were re-surveyed at the end of the month to measure the effect of this treatment, and at regular intervals throughout the study period to monitor treatment compliance. We find that Republicans who followed a liberal Twitter bot became substantially more conservative post-treatment, and Democrats who followed a conservative Twitter bot became slightly more liberal post-treatment. These findings have important implications for the interdisciplinary literature on political polarization as well as the emerging field of computational social science.Political polarization in the United States has become a central focus of social scientists in recent decades (1-7). Americans remain deeply divided on controversial issues such as inequality, race, and immigration. According to the 2016 National Election Study, 59.3% of Clinton voters believe federal aid to the poor should be increased compared to only 20.2% of Trump voters. 77.7% of Clinton voters express favorable attitudes towards the Black Lives Matter movement, whereas 31.2% of Trump voters do the same. 68.9% of Trump voters believe immigration to the United States should be decreased, compared to 21.9% of Clinton voters.Longstanding divides about these and many other issues have far-reaching consequences for the design and implementation of social policies as well as the effective function of democracy more broadly (8-12).America's deep partisan divides are often attributed to "echo chambers," or patterns of information sharing that reinforce pre-existing political beliefs by limiting exposure to heterogeneous ideas and perspectives (13)(14)(15)(16)(17). Concern about selective exposure to information and political polarization has increased in the age of social media (13,(18)(19)(20). The vast majority of Americans now visit a social media site at least once each day, and a rapidly growing number 2 of them list social media as their primary source of news (21). Despite initial optimism that social media might enable people to consume more heterogeneous sources of information about current events, there is growing concern that such forums exacerbate political polarization because of social network homophily, or the well-documented tendency of people to form social network ties to those who are similar to themselves (22, 23). The endogenous relationship between social network formation and political attitudes also creates formidable challenges f...

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Fear and Loathing across Party Lines: New Evidence on Group Polarization

Cited by 1,333 publications

References 51 publications

Social and economic ideologies differentially predict prejudice across the political spectrum, but social issues are most divisive.

Social and economic ideologies differentially predict prejudice across the political spectrum, but social issues are most divisive.

When do circumstances excuse? Moral prejudices and beliefs about the true self drive preferences for agency-minimizing explanations

Exposure to Opposing Views can Increase Political Polarization: Evidence from a Large-Scale Field Experiment on Social Media

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