Going to Extremes
Genes, Ideology, and Sophistication
Nathan Kalmoe & Martin Johnson
Journal of Experimental Political Science, forthcoming
Twin studies function as natural experiments that reveal political ideology’s substantial genetic roots, but how does that comport with research showing a largely nonideological public? This study integrates two important literatures and tests whether political sophistication -- itself heritable -- provides an “enriched environment” for genetic predispositions to actualize in political attitudes. Estimates from the Minnesota Twin Study show that sociopolitical conservatism is extraordinarily heritable (74%) for the most informed fifth of the public -- much more so than population-level results (57%) -- but with much lower heritability (29%) for the public’s bottom half. This heterogeneity is clearest in the Wilson–Patterson (W-P) index, with similar patterns for individual index items, an ideological constraint measure, and ideological identification. The results resolve tensions between two key fields by showing that political knowledge facilitates the expression of genetic predispositions in mass politics.
The measurement of partisan sorting for 180 million voters
Jacob Brown & Ryan Enos
Nature Human Behaviour, forthcoming
Segregation across social groups is an enduring feature of nearly all human societies and is associated with numerous social maladies. In many countries, reports of growing geographic political polarization raise concerns about the stability of democratic governance. Here, using advances in spatial data computation, we measure individual partisan segregation by calculating the local residential segregation of every registered voter in the United States, creating a spatially weighted measure for more than 180 million individuals. With these data, we present evidence of extensive partisan segregation in the country. A large proportion of voters live with virtually no exposure to voters from the other party in their residential environment. Such high levels of partisan isolation can be found across a range of places and densities and are distinct from racial and ethnic segregation. Moreover, Democrats and Republicans living in the same city, or even the same neighbourhood, are segregated by party.
Social Media, News Consumption, and Polarization: Evidence from a Field Experiment
American Economic Review, March 2021, Pages 831-870
Does the consumption of ideologically congruent news on social media exacerbate polarization? I estimate the effects of social media news exposure by conducting a large field experiment randomly offering participants subscriptions to conservative or liberal news outlets on Facebook. I collect data on the causal chain of media effects: subscriptions to outlets, exposure to news on Facebook, visits to online news sites, and sharing of posts, as well as changes in political opinions and attitudes. Four main findings emerge. First, random variation in exposure to news on social media substantially affects the slant of news sites that individuals visit. Second, exposure to counter-attitudinal news decreases negative attitudes toward the opposing political party. Third, in contrast to the effect on attitudes, I find no evidence that the political leanings of news outlets affect political opinions. Fourth, Facebook's algorithm is less likely to supply individuals with posts from counter-attitudinal outlets, conditional on individuals subscribing to them. Together, the results suggest that social media algorithms may limit exposure to counter-attitudinal news and thus increase polarization.
Drinking Alone: Local Socio-Cultural Degradation and Radical Right Support -- The Case of British Pub Closures
Comparative Political Studies, forthcoming
Little is known about how local context influences radical right voting. This paper advances the theory that the degradation of local socio-cultural hubs is linked to radical right support by contributing to loss of community and cultural identity. I examine this thesis by exploiting an original dataset on British community pub closures. I argue that the disappearance of community pubs triggers social isolation and signals the decline of the British working class condition, which is associated with UKIP support. Combining district-level data with UK panel data (2013–2016), I show that individuals living in districts that experience one additional community pub closure (relative to the total number of pubs per district) are more likely to support UKIP than any other party by 4.3 percentage points. The effect is magnified under conditions of material deprivation. This paper highlights the significance of local socio-cultural degradation as a mechanism to explain radical right support.
Interest group lobbying and partisan polarization in the United States: 1999–2016
Political Science Research and Methods, forthcoming
The lobbying activity of interest groups has been overlooked as a contributing factor to legislative party polarization in the United States. Using bill-level data from Congress and three state legislatures, I show floor votes on bills lobbied by more non-profit interest groups are more polarized by party. The state legislative data demonstrate the robustness of the relationship between lobbying and polarization, showing it is not an artifact of party agenda control, salience, or bill content. Increased lobbying from these groups in recent years helps explain high levels of partisan polarization in Congress and an uneven pattern across the state legislatures.
The ideological divide in confidence in science and participation in medical research
Matthew Gabel et al.
Scientific Reports, February 2021
In the United States, the wide ideological divergence in public confidence in science poses a potentially significant problem for the scientific enterprise. We examine the behavioral consequences of this ideological divide for Americans’ contributions to medical research. Based on a mass survey of American adults, we find that engagement in a wide range of medical research activities is a function of a latent propensity to participate. The propensity is systematically higher among liberals than among conservatives. A substantial part of this ideological divide is due to conservative Americans’ lower confidence in science. These findings raise important issues for the recruitment of subjects for medical studies and the generalizability of results from such studies.
Facial recognition technology can expose political orientation from naturalistic facial images
Scientific Reports, January 2021
Ubiquitous facial recognition technology can expose individuals’ political orientation, as faces of liberals and conservatives consistently differ. A facial recognition algorithm was applied to naturalistic images of 1,085,795 individuals to predict their political orientation by comparing their similarity to faces of liberal and conservative others. Political orientation was correctly classified in 72% of liberal–conservative face pairs, remarkably better than chance (50%), human accuracy (55%), or one afforded by a 100-item personality questionnaire (66%). Accuracy was similar across countries (the U.S., Canada, and the UK), environments (Facebook and dating websites), and when comparing faces across samples. Accuracy remained high (69%) even when controlling for age, gender, and ethnicity. Given the widespread use of facial recognition, our findings have critical implications for the protection of privacy and civil liberties.
Asking People to Explain Complex Policies Does Not Increase Political Moderation: Three Preregistered Failures to Closely Replicate Fernbach, Rogers, Fox, and Sloman’s (2013) Findings
Jarret Crawford & John Ruscio
Psychological Science, forthcoming
Fernbach et al. (2013) found that political extremism and partisan in-group favoritism can be reduced by asking people to provide mechanistic explanations for complex policies, thus making their lack of procedural-policy knowledge salient. Given the practical importance of these findings, we conducted two preregistered close replications of Fernbach et al.’s Experiment 2 (Replication 1a: N = 306; Replication 1b: N = 405) and preregistered close and conceptual replications of Fernbach et al.’s Experiment 3 (Replication 2: N = 343). None of the key effects were statistically significant, and only one survived a small-telescopes analysis. Although participants reported less policy understanding after providing mechanistic policy explanations, policy-position extremity and in-group favoritism were unaffected. That said, well-established findings that providing justifications for prior beliefs strengthens those beliefs, and well-established findings of in-group favoritism, were replicated. These findings suggest that providing mechanistic explanations increases people’s recognition of their ignorance but is unlikely to increase their political moderation, at least under these conditions.
Racial Politics and the Presidency: Analyzing White House Visits by Professional Sports Teams
Kendall Bailey & Austin Trantham
Social Science Quarterly, March 2021, Pages 897-919
Methods: Utilizing an original data set, we employ binary logistic regression to examine White House visits and objections by champions of six major professional sports leagues between 1993 and 2019.
Results: We find (1) increased visits and objections over time; (2) a negative relationship between a league's nonwhite composition and the likelihood of a White House visit; and (3) a positive relationship between a league's nonwhite composition and objections to visits with Republican presidents.
Some people just want to watch the world burn: The prevalence, psychology and politics of the ‘Need for Chaos’
Kevin Arceneaux et al.
Philosophical Transactions of the Royal Society: Biological Sciences, February 2021
People form political attitudes to serve psychological needs. Recent research shows that some individuals have a strong desire to incite chaos when they perceive themselves to be marginalized by society. These individuals tend to see chaos as a way to invert the power structure and gain social status in the process. Analysing data drawn from large-scale representative surveys conducted in Australia, Canada, the United Kingdom and the United States, we identify the prevalence of Need for Chaos across Anglo-Saxon societies. Using Latent Profile Analysis, we explore whether different subtypes underlie the uni-dimensional construct and find evidence that some people may be motivated to seek out chaos because they want to rebuild society, while others enjoy destruction for its own sake. We demonstrate that chaos-seekers are not a unified political group but a divergent set of malcontents. Multiple pathways can lead individuals to ‘want to watch the world burn’.
Urban–Rural Residential Mobility Associated With Political Party Affiliation: The U.S. National Longitudinal Surveys of Youth and Young Adults
Social Psychological and Personality Science, forthcoming
The current study used longitudinal panel data from the National Longitudinal Survey of Youth 1979 (NLSY79; n = 7,064) and National Longitudinal Survey of Young Adults (NLSY-YA; n = 2,985) to examine whether political party affiliation was related to residential mobility between rural regions, urban regions, and major cities in the United States. Over a follow-up of 4–6 years, stronger Republican affiliation was associated with lower probability of moving from rural regions to major cities (relative risk [RR] = 0.71, confidence interval [CI] = [0.54, 0.93]) and higher probability of moving away from major cities to urban or rural regions (RR = 1.17, CI = [1.03, 1.33]). The empirical correlation between party affiliation and urban–rural residence was r = −0.15 [−0.17, −0.13]. Simulated data based on the regression models produced a correlation of r = −0.06 [−0.10, −0.03], suggesting that selective residential mobility could account for almost half of the empirically observed association between party affiliation and urban–rural residence.
Measuring Congressional Partisanship and Its Consequences
Jeremy Gelman & Steven Lloyd Wilson
Legislative Studies Quarterly, forthcoming
We develop a method for measuring a legislator’s partisanship using their Twitter rhetoric. To do so, we classify over 2.1 million tweets sent during two congressional terms (2015 through 2018) to determine how often members use explicitly partisan language. Since lawmakers are strategic in how they communicate with the public, we argue our approach captures a member’s partisan intensity, the time and effort they devote to supporting their party. After validating our measure, we examine how partisanship affects commonly studied legislative behaviors. We show it predicts, independent of ideology, a lawmaker’s party‐unity voting and expressed bipartisanship. Additionally, we find that presidential support is principally driven by partisanship, not ideology. Our findings offer two contributions. First, we show that a member’s partisanship, based on how they talk about Democrats and Republicans online, is associated with their legislative behavior. Second, we measure a concept that is difficult to operationalize.
Do I support that it’s good or oppose that it’s bad? The effect of support-oppose framing on attitude sharing
Rhia Catapano & Zakary Tormala
Journal of Personality and Social Psychology, forthcoming
The rise of social media has led to unprecedented opportunities for individuals to share, or express, their attitudes on social and political issues. What factors affect whether individuals choose to share? This research identifies a novel determinant of attitude sharing — support-oppose framing, defined as whether individuals think of their own attitude in terms of what they support or what they oppose. Support-oppose framing is distinct from attitude valence, as the same attitude can be framed in terms of support (e.g., I support that this policy is bad) or opposition (e.g., I oppose that this policy is good). Seven experiments, two correlational studies, and one field study provide evidence for a support-oppose framing effect, whereby individuals are more likely to share attitudes framed in terms of positions they support rather than positions they oppose. This effect occurs via two pathways. In the first, support-framed attitudes are viewed as more value expressive, which facilitates greater attitude sharing. In the second, support-framed attitudes are believed to promote more positive impressions, which also leads to greater sharing. This effect is attenuated when individuals’ typical impression-management goals are relaxed.
“We Shall Overcome”: First-Person Plural Pronouns From Search Volume Data Predict Protest Mobilization Across the United States
Jais Adam-Troian, Eric Bonetto & Thomas Arciszewski
Social Psychological and Personality Science, forthcoming
Collective action is a key driver of social and political change within societies. So far, the main factor mobilizing individuals into collective action remains the extent to which they feel identified with a protesting group (i.e., social identification). Although the link between social identification and collective action is well-established, current evidence relies mostly on self-report data. To tackle this issue, we combined real-life protest counts in the United States (2017–2020) with online search data (Google Trends) for pronouns indicating a “group” mind-set (first-person plural pronouns; e.g., “we,” “us”). Time series analyses indicated that weekly fluctuations in searches (N = 164) predict both protest and protester counts over time. Confirmatory mixed models then showed that a 1% increase in pronoun searches was linked with +13.67% protests (95% CI [4.02, 23.32]) and +47.45% protesters (95% CI [26.54, 68.36]) the following week. These original results have important implications for the ecological study and quantification of collective action dynamics in psychology.
The Crowd-Emotion-Amplification Effect
Amit Goldenberg et al.
Psychological Science, March 2021, Pages 437-450
How do people go about reading a room or taking the temperature of a crowd? When people catch a brief glimpse of an array of faces, they can focus their attention on only some of the faces. We propose that perceivers preferentially attend to faces exhibiting strong emotions and that this generates a crowd-emotion-amplification effect — estimating a crowd’s average emotional response as more extreme than it actually is. Study 1 (N = 50) documented the crowd-emotion-amplification effect. Study 2 (N = 50) replicated the effect even when we increased exposure time. Study 3 (N = 50) used eye tracking to show that attentional bias to emotional faces drives amplification. These findings have important implications for many domains in which individuals must make snap judgments regarding a crowd’s emotionality, from public speaking to controlling crowds.
Bots are less central than verified accounts during contentious political events
Sandra González-Bailón & Manlio De Domenico
Proceedings of the National Academy of Sciences, 16 March 2021
Information manipulation is widespread in today’s media environment. Online networks have disrupted the gatekeeping role of traditional media by allowing various actors to influence the public agenda; they have also allowed automated accounts (or bots) to blend with human activity in the flow of information. Here, we assess the impact that bots had on the dissemination of content during two contentious political events that evolved in real time on social media. We focus on events of heightened political tension because they are particularly susceptible to information campaigns designed to mislead or exacerbate conflict. We compare the visibility of bots with human accounts, verified accounts, and mainstream news outlets. Our analyses combine millions of posts from a popular microblogging platform with web-tracking data collected from two different countries and timeframes. We employ tools from network science, natural language processing, and machine learning to analyze the diffusion structure, the content of the messages diffused, and the actors behind those messages as the political events unfolded. We show that verified accounts are significantly more visible than unverified bots in the coverage of the events but also that bots attract more attention than human accounts. Our findings highlight that social media and the web are very different news ecosystems in terms of prevalent news sources and that both humans and bots contribute to generate discrepancy in news visibility with their activity.