Individual talks: Emotions in and by groups

July 12th A2.09

The role of emotions on populist attitudes when encountering injustice

Ekaterina Lytkina & Arvid Kappas

Emotions play an important role in political attitudes and, likely, populism. We discuss why individuals sway to populist attitudes when facing a situation causing perceptions of relative deprivation. Relative deprivation is defined as upward comparisons due to a situation of injustice (Smith et al., 2012). Since populist ideology and communication involve an intergroup conflict between typically a corrupt and vicious elite and pure and homogeneous people (e.g., Mudde, 2004; Laclau, 2005), evaluations of fraternal, or group-level relative deprivations are expected to enhance individual’s position on populist attitudes. We hold that the relationship between the perceived fraternal relative deprivation and populist attitudes is mediated by emotions. Based on appraisal theory (e.g., Scherer, 2001), emotions emerging from the appraisal of an event causing perceptions of fraternal relative deprivation are predicted as well as how these emotions affect populist attitudes. For instance, anger should enhance populist attitudes, whereas sadness, anxiety, fear, or guilt should decrease them. Populist attitudes in this context refer to anti-elitism, popular sovereignty and homogeneity (Schulz et al., 2017). The results of two experiments will be presented that study the impact of perceived relative deprivation and the role of emotions in this process with regard to attitudes and behaviors.

Collective Emotions and Social Resilience in the Digital Traces After a Terrorist Attack

David Garcia & Bernard Rimé

After collective traumas like natural disasters and terrorist attacks, members of concerned communities experience intense emotions and talk profusely about them. While these exchanges resemble simple emotional venting, we hypothesized them to represent a peer-to-peer analogue of Durkheim’s (1912) theory of emotional effervesce in collective gatherings: participants' reciprocal emotion stimulation would lead to higher levels of solidarity in the community. We present a large-scale test of our extension of Durkheim's theory through the analysis of the content of peer-to-peer interactions in the aftermath of the Paris terrorist attacks of November, 2015. We collected more than 17 Million tweets generated by 62,114 individuals that we analyzed through the French adaptation of the Linguistic Inquiry and Word Count method. We applied an agent-based modelling approach to explain how collective emotions are built on individual emotional experiences and social sharing of emotions. We found a collective negative emotional response followed by a marked long-term increase in the use of lexical indicators related to solidarity. Expressions of social processes, prosocial behavior, and positive affect were higher in the months following the attacks for the individuals who participated to a higher degree in the collective emotion. These effects can be observed in the online visualization of our analysis: http://dgarcia.eu/ParisAttacks.html Our findings support the conclusion that the social sharing of emotions after a disaster is associated with higher solidarity, revealing the social resilience of a community. More details of the research questions, data, and analysis of this submission can be found in the PsyArxiv preprint: https://psyarxiv.com/8envw/

Social Sharing of Political Emotions in Online Populist Communications

Philipp Wunderlich

Anger and anxiety are frequently considered driving forces of populist party support since their corresponding appraisal structures resonate with characteristics of populist “thin” ideologies. This contribution examines the presence and diffusion of these emotions in populist online communications to gain insights into the formation of intergroup emotions. The study applies a lexical sentiment analysis of discrete emotions to a sample of 275.582 Twitter posts authored by officials of two German political parties frequently characterized as “populist”, the left-wing “Die Linke” and the right-wing “Alternative für Deutschland”, and a baseline sample of 315,536 random posts. Using multilevel regression models, the study compares the presence of anger and anxiety cues across groups and analyses associations between these cues and linguistic references to immigrants and political elites. Also, the effect of expressed anger on the frequency by which posts are shared by their recipients is modelled. Results support the hypotheses that anger, and to a lesser extent anxiety, are dominant emotions in populist communications on Twitter and that populists are more likely to evoke anger when referring to out-groups. Finally, the study shows that anger cues promote the sharing of posts and that this effect is significantly stronger for populist posts. Since social sharing of emotions is thought to contribute to emotional alignment processes within groups and consequently to the strengthening of group identities, these findings do not only depict a strong resonance of emotionalized populist messages promoting out-group devaluation but also hint at their potential to foster in-group cohesion within populist online-collectives.

Analysing affective dynamics through sentiment in social media status updates

Max Pellert, Simon Schweighofer & David Garcia

Quantifying the temporal dynamics of emotions is important to understand the role of affect in well-being. The way emotional states change is commonly analyzed through self-reports (for example in Kuppens, Oravecz, & Tuerlinckx, 2010), gathering temporal sequences of emotions over periods of few days. However, self-reports pose limits to the length of the observation period and to the amount of participants that can be included in a study. The analysis of social media data poses an alternative way to capture affective dynamics at longer timescales and in large samples of individuals. We studied a dataset of more than 22 Million Facebook status updates donated by more than 150,000 individuals, spanning observation periods of 1.5 years on average. We applied sentiment analysis and computerized psycholinguistic methods to quantify expressed emotions in terms of valence and arousal, and analysed the resulting trajectories of emotions through a dynamical system model. Our results confirm the existence of an affective baseline of positive valence and neutral arousal that attracts emotional states. We quantified further the attractor strength towards this baseline and the affective variability of emotions across individuals. These results show how observational large-scale analyses can provide alternative evidence to traditional experimental and survey methods, providing a new way to test hypotheses in affective science. Kuppens, P., Oravecz, Z., & Tuerlinckx, F. (2010). Feelings change: Accounting for individual differences in the temporal dynamics of affect. Journal of Personality and Social Psychology, 99(6), 1042–1060. https://doi.org/10.1037/a0020962