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Publications

Below you will find some of our recent publications. Happy readings and do get in touch with any thoughts, questions or ideas for collaborations.

During political campaigns, candidates use rhetoric to advance competing visions and assessments of their country. Research reveals that the moral language used in this rhetoric can significantly influence citizens’ political attitudes and behaviors; however, the moral language actually used in the rhetoric of elites during political campaigns remains understudied. Using a data set of every tweet (⁠N=139,412�=139,412⁠) published by 39 US presidential candidates during the 2016 and 2020 primary elections, we extracted moral language and constructed network models illustrating how candidates’ rhetoric is semantically connected. These network models yielded two key discoveries. First, we find that party affiliation clusters can be reconstructed solely based on the moral words used in candidates’ rhetoric. Within each party, popular moral values are expressed in highly similar ways, with Democrats emphasizing careful and just treatment of individuals and Republicans emphasizing in-group loyalty and respect for social hierarchies. Second, we illustrate the ways in which outsider candidates like Donald Trump can separate themselves during primaries by using moral rhetoric that differs from their parties’ common language. Our findings demonstrate the functional use of strategic moral rhetoric in a campaign context and show that unique methods of text network analysis are broadly applicable to the study of campaigns and social movements.

During political campaigns, candidates use rhetoric to advance competing visions and assessments of their country. Research reveals that the moral language used in this rhetoric can significantly influence citizens’ political attitudes and behaviors; however, the moral language actually used in the rhetoric of elites during political campaigns remains understudied. Using a data set of every tweet (⁠N=139,412�=139,412⁠) published by 39 US presidential candidates during the 2016 and 2020 primary elections, we extracted moral language and constructed network models illustrating how candidates’ rhetoric is semantically connected. These network models yielded two key discoveries. First, we find that party affiliation clusters can be reconstructed solely based on the moral words used in candidates’ rhetoric. Within each party, popular moral values are expressed in highly similar ways, with Democrats emphasizing careful and just treatment of individuals and Republicans emphasizing in-group loyalty and respect for social hierarchies. Second, we illustrate the ways in which outsider candidates like Donald Trump can separate themselves during primaries by using moral rhetoric that differs from their parties’ common language. Our findings demonstrate the functional use of strategic moral rhetoric in a campaign context and show that unique methods of text network analysis are broadly applicable to the study of campaigns and social movements.

Updating one’s beliefs about the causes and effects of climate change is crucial for altering attitudes and behaviours. Importantly, metacognitive abilities - insight into the (in)correctness of one’s beliefs- play a key role in the formation of polarised beliefs. We here aimed at investigated the role of metacognition in changing beliefs about climate change. To that end, we focused on the role of domain-general and domain-specific metacognition in updating prior beliefs about climate change across the spectrum of climate change scepticism. We also considered the role of how climate science is communicated in the form of textual or visuo-textual presentations. We asked two large US samples to perform a perceptual decision-making task (to assess domain-general decision-making and metacognitive abilities. They next performed a belief-updating task, where they were exposed to good and bad news about climate change and we asked them about their beliefs and their updating. Lastly, they completed a series of questionnaires probing their attitudes to climate change. We show that climate change scepticism is associated with differences in domain-general as well as domain-specific metacognitive abilities. Moreover, domain-general metacognitive sensitivity influenced belief updating in an asymmetric way: lower domain-general metacognition decreased the updating of prior beliefs, especially in the face of negative evidence. Our findings highlight the role of metacognitive failures in revising erroneous beliefs about climate change and point to their adverse social effects.

We review findings and hypotheses at the intersections of life sciences, social sciences and humanities to shed light on how and why people come to experience such emotions in politics and what if any are their behavioural consequences. To answer these questions, we provide insights from predictive coding accounts of interoception and emotion and a proof of concept experiment to highlight the role of visceral states in political behaviour.

Politics is visceral

In an age thick with anger and fear, we might dream of a purely rational politics but it would be a denial of our humanity.

On the realness of people who do not exist: the social processing of artificial faces

Today more than ever, we are asked to judge the realness, truthfulness and trustworthiness of our social world. We here focus on how people perceive artificially-generated faces. Generative adversarial networks (GANs) faces are realistic-looking faces of non-existing people, increasingly used in marketing, journalism, social media, and political propaganda. Across three studies, we investigated if and how participants can distinguish between GAN and Real faces and the social consequences of exposure to artificial faces. GAN faces were more likely to be perceived as real than Real faces, a pattern partly explained by certain intrinsic stimuli characteristics. Moreover, participants’ realness judgments influenced their behaviour, displaying increased social conformity towards faces perceived as real, independently of their actual realness. Lastly, knowledge about the existence of GAN faces eroded social trust. Our findings point to the potentially far-reaching consequences of the ubiquitous use of GAN faces in a culture powered by images at unprecedented levels.

Computational and neurocognitive approaches to the political brain: key insights and future avenues for political neuroscience

Although the study of political behaviour has been traditionally restricted to the social sciences, new advances in political neuroscience and computational cognitive science highlight that the biological sciences can offer crucial insights into the roots of ideological thought and action. Echoing the dazzling diversity of human ideologies, this theme issue seeks to reflect the multiplicity of theoretical and methodological approaches to understanding the nature of the political brain. Cutting-edge research along three thematic strands is presented, including (i) computational approaches that zoom in on fine-grained mechanisms underlying political behaviour, (ii) neurocognitive perspectives that harness neuroimaging and psychophysiological techniques to study ideological processes, and (iii) behavioural studies and policy-minded analyses of such understandings across cultures and across ideological domains. Synthesizing these findings together, the issue elucidates core questions regarding the nature of uncertainty in political cognition, the mechanisms of social influence and the cognitive structure of ideological beliefs. This offers key directions for future biologically grounded research as well as a guiding map for citizens, psychologists and policymakers traversing the uneven landscape of modern polarization, misinformation, intolerance and dogmatism.

Angry Politics: How experienced anger shifts political leader choices

Past research has shown that anger is associated with support for confrontational and punitive responses during crises, and with endorsement of authoritarian ideologies. One important question is whether it is the political origin of the feeling of anger that explains the association between anger and authoritarianism or whether any feeling of anger would be associated with changes in political attitudes. Here, we tested the effect of non-politically motivated incidental anger on the preference for strong leaders. In line with past research, we predicted that anger would increase preferences for authoritarian leaders. Across three experiments, we exposed participants to an anger manipulation. Before and after this manipulation, we measured participants’ political leader preferences by asking them to choose between the faces of two leaders they would vote for in a hypothetical election. The level of self-reported anger predicted the probability of choosing more dominant and less trustworthy leaders after the manipulation, suggesting that even non-political incidental anger increases preferences for authoritarian leaders. Importantly, this change was absent when participants had to indicate which individuals were perceived as most successful, documenting the specificity of our results in the context of political leaders.

How should the political animals of the 21st century feel?: Comment on “The sense of should: A biologically-based framework for modelling social pressure” by J.E. Theriault et al.

A commentary on the  seminal article by  Theriault, Young and Feldman Barrett [1] that puts put forward a wide-ranging model that accounts for a fundamental building block of our sociality, namely the felt sense that we must conform to other people's expectations, what they aptly call ‘the sense of should’. 

[1] J.E. Theriault, L. Young, L.F. Barrett (2021) The sense of should: a biologically-based framework for modeling social pressure.  Phys Life Rev, 36 (2021), pp. 100-136, 10.1016/j.plrev.2020.01.004

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