The current coronavirus disease 2019 (COVID-19) pandemic elicits a vast amount of anxiety. In the current study, we investigated how anxiety related to COVID-19 is associated with support for and compliance with governmental hygiene measures, and how these are influenced by populist attitudes, anger at the government, and conspiracy mentalities. We conducted an online survey in April 2020 in four different countries (Germany, the Netherlands, Spain, and the UK; N = 2,031) using a cross-sectional design. Results showed that (1) anxiety related to COVID-19 is associated with conspiracy beliefs, anger at the government, and populist attitudes, and (2) support for and compliance with hygiene measures are both positively predicted by anxiety related to COVID-19; however, (3) support for hygiene measures is also predicted by populist attitudes and negatively by conspiracy mentalities, whereas compliance with hygiene measures is more strongly predicted by anger at transgressors (anger at people transgressing the hygiene measures). Consequently, although anxiety related to COVID-19 concerns the health of individual people, it also has political and social implications: anxiety is associated with an increase in anger, either at transgressors or the government.
Previous research on predictors of populism has predominantly focused on socio-economic (e.g., education, employment, social status), and socio-cultural factors (e.g., social identity and social status). However, during the last years, the role of negative emotions has become increasingly prominent in the study of populism. We conducted a cross-national survey in 15 European countries (N=8059), measuring emotions towards the government and the elites, perceptions of threats about the future, and socio-economic factors as predictors of populist attitudes (the latter operationalized via three existing scales, anti-elitism, Manichaean outlook, people-centrism, and a newly developed scale on nativism). We tested the role of emotional factors in a deductive research design based on a structural model. Our results show that negative emotions (anger, contempt and anxiety) are better predictors of populist attitudes than mere socio-economic and socio-cultural factors. An inductive machine learning algorithm, Random Forest (RF), reaffirmed the importance of emotions across our survey dataset.
There has been an increased interest in modelling political discourse within the natural language processing (NLP) community, in tasks such as political bias and misinformation detection, among others. Metaphor-rich and emotion-eliciting communication strategies are ubiquitous in political rhetoric, according to social science research. Yet, none of the existing computational models of political discourse has incorporated these phenomena. In this paper, we present the first joint models of metaphor, emotion and political rhetoric, and demonstrate that they advance performance in three tasks: predicting political perspective of news articles, party affiliation of politicians and framing of policy issues.
Computational modelling of political discourse tasks has become an increasingly important area of research in natural language processing. Populist rhetoric has risen across the political sphere in recent years; however, computational approaches to it have been scarce due to its complex nature. In this paper, we present the new Us vs. Them dataset, consisting of 6861 Reddit comments annotated for populist attitudes and the first large-scale computational models of this phenomenon. We investigate the relationship between populist mindsets and social groups, as well as a range of emotions typically associated with these. We set a baseline for two tasks related to populist attitudes and present a set of multi-task learning models that leverage and demonstrate the importance of emotion and group identification as auxiliary tasks.
This study analyzes the mainstream media coverage on Germany’s integration debate between 2009 and 2014, while detecting main debate actors, topics, discourses, key events and their relations to one another. Media representations of Muslims, integration, immigration, multiculturalism and creation of otherness are scrutinized, considering different political alignments of mainstream newspapers. Furthermore, the Sarrazin debate is contextualized within recent events such as right-wing populism and anti-Islamization movements. A quantitative content analysis revealed pragmatism and culturalism as the leading discourses in one-third of all left and right leaning newspapers, while integration, immigration and populist language in politics were the most discussed topics. Mainly, events and actors related to the Sarrazin debate were mentioned. We argue that the Sarrazin debate has encouraged a variety of actors to speak out in favor or against Muslims. Our findings suggest a personal network analysis combined with qualitative research, in order to identify more actors, ties and network alliances.
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