Ideological Social Identity: Psychological Attachment to Ideological In-Groups as a Political Phenomenon and a Behavioral Influence

Devine, Christopher J.

doi:10.1007/s11109-014-9280-6

Cited by 116 publications

(74 citation statements)

References 42 publications

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“…For instance, research on priming effects shows that exposure to minimal partisan cues, such as party logos, can activate partisan biases in response to novel information (41)(42)(43). Moreover, recent public opinion research suggests that biased assimilation is not driven by contact with opposing beliefs but rather by political identity signaling, in which confrontation with individuals who belong to an opposing partisan group strengthens subjects' partisan biases (44)(45)(46)(47)(48). A key limitation of prior experiments on political polarization and belief exchange in bipartisan networks is that the effects of partisan priming and political identity cannot be excluded from face-to-face discussion groups, in which people are exposed to opposing views and partisan cues simultaneously (18-20, 25, 26).…”

mentioning

confidence: 99%

Social learning and partisan bias in the interpretation of climate trends

Guilbeault

Becker

Centola

2018

Proc. Natl. Acad. Sci. U.S.A.

193

115

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Vital scientific communications are frequently misinterpreted by the lay public as a result of motivated reasoning, where people misconstrue data to fit their political and psychological biases. In the case of climate change, some people have been found to systematically misinterpret climate data in ways that conflict with the intended message of climate scientists. While prior studies have attempted to reduce motivated reasoning through bipartisan communication networks, these networks have also been found to exacerbate bias. Popular theories hold that bipartisan networks amplify bias by exposing people to opposing beliefs. These theories are in tension with collective intelligence research, which shows that exchanging beliefs in social networks can facilitate social learning, thereby improving individual and group judgments. However, prior experiments in collective intelligence have relied almost exclusively on neutral questions that do not engage motivated reasoning. Using Amazon's Mechanical Turk, we conducted an online experiment to test how bipartisan social networks can influence subjects' interpretation of climate communications from NASA. Here, we show that exposure to opposing beliefs in structured bipartisan social networks substantially improved the accuracy of judgments among both conservatives and liberals, eliminating belief polarization. However, we also find that social learning can be reduced, and belief polarization maintained, as a result of partisan priming. We find that increasing the salience of partisanship during communication, both through exposure to the logos of political parties and through exposure to the political identities of network peers, can significantly reduce social learning.

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mentioning

confidence: 99%

Social learning and partisan bias in the interpretation of climate trends

Guilbeault

Becker

Centola

2018

Proc. Natl. Acad. Sci. U.S.A.

193

115

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“…Following the previous research (e.g., Ellis and Stimson, ), we distinguish between symbolic ideology and operational ideology. The former type of ideology more closely approximates the group‐based, psychological attachments that constitute a social identity (Conover and Feldman, ; Malka and Llekes, ; Devine, ; Kinder and Kalmoe, ), whereas the latter form of ideology constitutes a composite score of policy preferences. We operationalize liberal–conservative identity using the traditional self‐placement instrument in which individuals are asked to select the category that best describes their ideological preferences.…”

Section: Methods and Resultsmentioning

confidence: 99%

Affective Consistency and Sorting

Davis

Klar

Weber

2019

Social Science Quarterly

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Objective. Sorting is often portrayed as a mechanistic response to elite polarization: individuals recognize salient differences between the parties and match their preferences accordingly. Much less is known, however, about the psychological and motivational processes that contribute to it. In particular, how might affective reactions to elites shape convergence among political preferences? Method. To explore the relationship between the consistency of self-reported affect and sorting, we analyze cross-sectional and panel data from the American National Election Studies. Results. On balance, we find that negative emotions directed toward the opposing party candidate and positive emotions toward one's own party candidate are associated with an increase in the alignment of ideological and partisan preferences. Conclusion. These findings illustrate how affect contributes to consistency in mass opinion.

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“…This distinction is nontrivial. Research demonstrates that both partisanship (Greene 2004;Huddy, Mason, and Aaore 2015) and liberalconservative self-placement function as forms of social identity (Devine 2015;Mason 2018;Davis 2018). That is, individuals conceptualize their political orientations relationally, assigning positive (negative) emotional value to the in-group (out-group).…”

Section: Changes In the Centrality Of Symbolic And Operational Contentmentioning

confidence: 99%

Change We Can Believe In: Structural and Content Dynamics within Belief Networks

Fishman¹,

Davis²

2019

Preprint

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Presumably, network analysis supplies an analytical framework for exploring the empirical properties of ideology. This manuscript incorporates two important, though ignored features in past research by inves- tigating how time shapes the properties of belief networks for different populations of people – those who exhibit high and low levels of political knowledge. Subsequent analysis produces several findings: (1) belief network density increases asymmetrically among people with high relative to low knowledge; (2) symbolic preferences are always more central to belief networks irrespective of survey timing or popula- tion; in contrast, policy beliefs exhibit some increase in centrality over time among the politically knowl- edgeable; and, (3) centrality does not predict variance within standard parametric models. This latter finding, in particular, presents problems for describing belief networks using the vernacular of Conversian belief systems – a disconnect that seems grounded in the mismatch between Converse’s individual-level theory and network analysis’ population-based properties.

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Ideological Social Identity: Psychological Attachment to Ideological In-Groups as a Political Phenomenon and a Behavioral Influence

Cited by 116 publications

References 42 publications

Social learning and partisan bias in the interpretation of climate trends

Social learning and partisan bias in the interpretation of climate trends

Affective Consistency and Sorting

Change We Can Believe In: Structural and Content Dynamics within Belief Networks

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