End Times
Meaningful outrage: Anger at injustice bolsters meaning for justice sensitive individuals
Zachary Rothschild & Lucas Keefer
European Journal of Social Psychology, forthcoming
Abstract:
Individuals are frequently exposed to media describing salient moral violations, often eliciting negative reactions. Three studies examined whether the outrage engendered by such news may serve as a source of personal meaning for justice sensitive individuals. Using an experience sampling method, Study 1 found that among high (but not low) justice sensitive individuals, outrage (but not sadness) at unethical/unjust news content predicted greater personal meaning. Employing an experimental paradigm, Study 2 found that the opportunity to express outrage at third-party harm-doing attenuated a threat-induced reduction in personal meaning among high (but not low) justice sensitive participants. Study 3 found that giving justice sensitive participants the opportunity to affirm the meaningfulness of their own life (vs. another person's life or no affirmation) reduced expressions of outrage at third-party harm-doing. Results suggest outrage may uniquely serve a meaning-maintenance function for those who view upholding justice as a central value.
Economic Interests, Worldviews, and Identities: Theory and Evidence on Ideational Politics
Elliott Ash, Sharun Mukand & Dani Rodrik
NBER Working Paper, November 2021
Abstract:
We distinguish between ideational and interest-based appeals to voters on the supply side of politics, and integrate the Keynes-Hayek perspective on the importance of ideas with the Stigler-Becker approach emphasizing vested interests. In our model, political entrepreneurs discover identity and worldview “memes” (narratives, cues, frames) that shift beliefs about voters’ identities or their views of how the world works. We identify a complementarity between worldview politics and identity politics and illustrate how they may reinforce each other. Furthermore, we show how adverse economic shocks may result in a greater incidence of ideational politics. We use these results to analyze data on 60,000 televised political ads in U.S. localities over the years 2000 through 2018. Our empirical work quantifies ideational politics and provides support for the key model implications, including the impact of higher inequality on both identity and worldview politics.
Algorithmic amplification of politics on Twitter
Ferenc Huszár et al.
Proceedings of the National Academy of Sciences, 4 January 2022
Abstract:
Content on Twitter’s home timeline is selected and ordered by personalization algorithms. By consistently ranking certain content higher, these algorithms may amplify some messages while reducing the visibility of others. There’s been intense public and scholarly debate about the possibility that some political groups benefit more from algorithmic amplification than others. We provide quantitative evidence from a long-running, massive-scale randomized experiment on the Twitter platform that committed a randomized control group including nearly 2 million daily active accounts to a reverse-chronological content feed free of algorithmic personalization. We present two sets of findings. First, we studied tweets by elected legislators from major political parties in seven countries. Our results reveal a remarkably consistent trend: In six out of seven countries studied, the mainstream political right enjoys higher algorithmic amplification than the mainstream political left. Consistent with this overall trend, our second set of findings studying the US media landscape revealed that algorithmic amplification favors right-leaning news sources. We further looked at whether algorithms amplify far-left and far-right political groups more than moderate ones; contrary to prevailing public belief, we did not find evidence to support this hypothesis. We hope our findings will contribute to an evidence-based debate on the role personalization algorithms play in shaping political content consumption.
Sincere or Motivated? Partisan Bias in Non-Political Information Processing
Yunhao Zhang & David Rand
MIT Working Paper, December 2021
Abstract:
Political divisions have become a central feature of modern life. Here, we ask whether these divisions affect performance outside the context of politics. Indeed, in an incentivized non-political news assessment task, we find that subjects are less swayed by (accurate) information that comes from a counter-partisan compared to from a co-partisan. We then adjudicate between two possible mechanisms for this biased advice-taking: a preference-based account, where subjects are motivated to take less advice from counter-partisans because doing so is unpleasant; versus a belief-based account, where subjects sincerely believe co-partisans are more competent at the task (even though this belief is incorrect). To do so, we examine the impact of a 1000-fold increase in the stakes, which should increase accuracy motivations (and thereby reduce the relative impact of partisan motivations). We find that increasing the stakes does not reduce biased advice-taking. We also find that subjects (incorrectly) believe that co-partisans are better at the task, and that this incorrect belief is not reduced by raising the stakes of the belief elicitation. Finally, we find that subjects readily correct their misbelief that co-partisans perform better on the task after being given corrective feedback. These findings support a belief-based, rather than a preference-based, account of politically biased advice-taking, with important implications for understanding partisan bias and improving workplace collaboration.
The nonlinear feedback dynamics of asymmetric political polarization
Naomi Ehrich Leonard et al.
Proceedings of the National Academy of Sciences, 14 December 2021
Abstract:
Using a general model of opinion dynamics, we conduct a systematic investigation of key mechanisms driving elite polarization in the United States. We demonstrate that the self-reinforcing nature of elite-level processes can explain this polarization, with voter preferences accounting for its asymmetric nature. Our analysis suggests that subtle differences in the frequency and amplitude with which public opinion shifts left and right over time may have a differential effect on the self-reinforcing processes of elites, causing Republicans to polarize more quickly than Democrats. We find that as self-reinforcement approaches a critical threshold, polarization speeds up. Republicans appear to have crossed that threshold while Democrats are currently approaching it.
The Role of Social Signaling in Selective Exposure to Information
Molly Moore, Charles Dorison & Julia Minson
Harvard Working Paper, October 2021
Abstract:
Effective judgment and decision making demands exposure to diverse information. Yet, a large interdisciplinary literature makes clear that individuals often avoid information that contradicts their prior beliefs, a tendency referred to as selective exposure. Prior research has focused on intrapersonal drivers of selective exposure, including avoidance of cognitive dissonance. We take a complementary approach by investigating the interpersonal drivers of selective exposure. Drawing on the fact that individuals care deeply about their reputations, we test a social signaling model of selective exposure, hypothesizing that (1) individuals shift their information consumption choices to signal to observers and (2) observers reward such shifts. In the context of partisan politics in the United States, three financially-incentivized, pre-registered experiments (N = 2,325) supported both hypotheses. Our results also identified three moderating factors: the type of interaction the observers expect to have with the actors, congruence of group membership between actors and observers (aligned vs. unaligned), and the magnitude of selective exposure. These results suggest that tailoring one’s information consumption choices has strategic value. Importantly, examining the reputational causes and consequences of selective exposure reveals a novel trade-off: what is typically optimal for decision quality may conflict with accomplishing one’s reputation-management goals. In the era of social media, when information consumption choices are more public than ever before, understanding the ways in which reputational considerations shape decision making illuminates not only why selective exposure remains so pervasive, but also suggests novel mitigation strategies.
Multidimensional polarization dynamics in US election data in the long term (2012–2020) and in the 2020 election cycle
Alejandro Dinkelberg et al.
Analyses of Social Issues and Public Policy, December 2021, Pages 284-311
Abstract:
We use a network-based method to explore bifurcation in the multidimensional opinion-based political identity structure from 2012 to 2020 in American National Election Studies data. We define polarization as ideological clustering which occurs when attitudes are linked or aligned across group-relevant dimensions. We identify relevant dimensions with a theory-driven approach and confirm them with the data-driven Boruta method, validating the importance of these items for self-reported political identity in these samples. To account for data sets having different sizes, we bootstrapped to obtain comparable samples. For each, a bipartite projection generates a network where edges represent similarity in responses between dyads. The data provide us with preidentified groups (Republicans and Democrats). We use them as our network communities and to calculate an edge-based polarization. Results show bifurcation progressively increasing, with a striking increase from 2016 to 2020. We visualize these identity-related shifts in opinion structure over time and discuss how polarization results from both between- and within-group dynamics. We apply a similar method to a smaller data set (N = 294) to explore short-term fluctuations before and after the 2020 election. Results suggest that between-group polarization is more evident after than before the election, because in-group opinion dynamics result in a more synchronized opinion-space for Republicans.
Polarization and tipping points
Michael Macy et al.
Proceedings of the National Academy of Sciences, 14 December 2021
Abstract:
Research has documented increasing partisan division and extremist positions that are more pronounced among political elites than among voters. Attention has now begun to focus on how polarization might be attenuated. We use a general model of opinion change to see if the self-reinforcing dynamics of influence and homophily may be characterized by tipping points that make reversibility problematic. The model applies to a legislative body or other small, densely connected organization, but does not assume country-specific institutional arrangements that would obscure the identification of fundamental regularities in the phase transitions. Agents in the model have initially random locations in a multidimensional issue space consisting of membership in one of two equal-sized parties and positions on 10 issues. Agents then update their issue positions by moving closer to nearby neighbors and farther from those with whom they disagree, depending on the agents’ tolerance of disagreement and strength of party identification compared to their ideological commitment to the issues. We conducted computational experiments in which we manipulated agents’ tolerance for disagreement and strength of party identification. Importantly, we also introduced exogenous shocks corresponding to events that create a shared interest against a common threat (e.g., a global pandemic). Phase diagrams of political polarization reveal difficult-to-predict transitions that can be irreversible due to asymmetric hysteresis trajectories. We conclude that future empirical research needs to pay much closer attention to the identification of tipping points and the effectiveness of possible countermeasures.
Ownership, Partisanship and Media Slant: Evidence from the U.S. Media during the Sino-U.S. Trade Conflict
Meng Wu
Boston University Working Paper, November 2021
Abstract:
I explore what determines media slant towards foreign nations using the 2018-2019 Sino-U.S. trade negotiation as a testing ground. Using an event study design and coverage by local U.S. newspapers, I analyze how stories about China respond to shifts of U.S. policy towards China, and how this media reaction is determined by owners’ partisan affinity, controlling for readers’ characteristics. I find that local newspapers with Republican-leaning owners increase the intensity of negative coverage following a shift towards hostile trade policies relative to papers of nonpartisan owners, and they decrease this slant following a conciliatory shift; the opposite is true for Democratic-leaning media owners. To address the potential endogeneity of diplomatic events, I select events that induced significant abnormal price fluctuations of trade-war-related financial securities. I further establish a causal effect of owners’ preferences by exploiting mergers and acquisitions among national conglomerates as a source of variation in political orientation of owners. These findings imply a spillover from domestic policy in the formation of citizens’ sentiment towards other nations: the media, as their lens to view the world, is colored by domestic political polarization.
Inequality, identity, and partisanship: How redistribution can stem the tide of mass polarization
Alexander Stewart, Joshua Plotkin & Nolan McCarty
Proceedings of the National Academy of Sciences, 14 December 2021
Abstract:
The form of political polarization where citizens develop strongly negative attitudes toward out-party members and policies has become increasingly prominent across many democracies. Economic hardship and social inequality, as well as intergroup and racial conflict, have been identified as important contributing factors to this phenomenon known as “affective polarization.” Research shows that partisan animosities are exacerbated when these interests and identities become aligned with existing party cleavages. In this paper, we use a model of cultural evolution to study how these forces combine to generate and maintain affective political polarization. We show that economic events can drive both affective polarization and the sorting of group identities along party lines, which, in turn, can magnify the effects of underlying inequality between those groups. But, on a more optimistic note, we show that sufficiently high levels of wealth redistribution through the provision of public goods can counteract this feedback and limit the rise of polarization. We test some of our key theoretical predictions using survey data on intergroup polarization, sorting of racial groups, and affective polarization in the United States over the past 50 y.
Quantifying social organization and political polarization in online platforms
Isaac Waller & Ashton Anderson
Nature, 9 December 2021, Pages 264–268
Abstract:
Mass selection into groups of like-minded individuals may be fragmenting and polarizing online society, particularly with respect to partisan differences. However, our ability to measure the social makeup of online communities and in turn, to understand the social organization of online platforms, is limited by the pseudonymous, unstructured and large-scale nature of digital discussion. Here we develop a neural-embedding methodology to quantify the positioning of online communities along social dimensions by leveraging large-scale patterns of aggregate behaviour. Applying our methodology to 5.1 billion comments made in 10,000 communities over 14 years on Reddit, we measure how the macroscale community structure is organized with respect to age, gender and US political partisanship. Examining political content, we find that Reddit underwent a significant polarization event around the 2016 US presidential election. Contrary to conventional wisdom, however, individual-level polarization is rare; the system-level shift in 2016 was disproportionately driven by the arrival of new users. Political polarization on Reddit is unrelated to previous activity on the platform and is instead temporally aligned with external events. We also observe a stark ideological asymmetry, with the sharp increase in polarization in 2016 being entirely attributable to changes in right-wing activity. This methodology is broadly applicable to the study of online interaction, and our findings have implications for the design of online platforms, understanding the social contexts of online behaviour, and quantifying the dynamics and mechanisms of online polarization.
Reducing opinion polarization: Effects of exposure to similar people with differing political views
Stefano Balietti et al.
Proceedings of the National Academy of Sciences, 28 December 2021
Abstract:
In a large-scale, preregistered experiment on informal political communication, we algorithmically matched participants, varying two dimensions: 1) the degree of incidental similarity on nonpolitical features; and 2) their stance agreement on a contentious political topic. Matched participants were first shown a computer-generated social media profile of their match highlighting all the shared nonpolitical features; then, they read a short, personal, but argumentative, essay written by their match about the reduction of inequality via redistribution of wealth by the government. We show that support for redistribution increased and polarization decreased for participants with both mild and strong views, regardless of their political leaning. We further show that feeling close to the match is associated with an 86% increase in the probability of assimilation of political views. Our analysis also uncovers an asymmetry: Interacting with someone with opposite views greatly reduced feelings of closeness; however, interacting with someone with consistent views only moderately increased them. By extending previous work about the effects of incidental similarity and shared identity on affect into the domain of political opinion change, our results bear real-world implications for the (re)-design of social media platforms. Because many people prefer to keep politics outside of their social networks, encouraging cross-cutting political communication based on nonpolitical commonalities is a potential solution for fostering consensus on potentially divisive and partisan topics.