Aktuelle Publikationen

Polarization is threatening the stability of democratic societies. Until now, polarization research has focused on opinion extremeness, overlooking the correlation between different policy issues. In this paper, we explain the emergence of hyperpolarization, i.e., the combination of extremeness and correlation between issues, by developing a new theory of opinion formation called "Weighted Balance Theory (WBT)". WBT extends Heider's cognitive balance theory to encompass multiple weighted attitudes. We validated WBT on empirical data from the 2016 National Election Survey. Furthermore, we developed an opinion dynamics model based on WBT, which, for the first time, is able to generate hyperpolarization and to explain the link between affective and opinion polarization. Finally, our theory encompasses other phenomena of opinion dynamics, including mono-polarization and backfire effects.

The article deals with the widely neglected employment relations in the public sector of Germany with a special focus on civil servants. It is subdivided into two main parts. A shorter part elaborates on public employees and collective bargaining, a longer one on civil servants and their diverging forms of employment relations without the right to collective bargaining and strike. In order to better understand major changes that have taken place since the mid2000s, we chose a long‐term perspective and examine traditional as well as present forms of interest representation. Limited degrees of decentralisation and their lasting diverging consequences are analysed in great detail.

We analyze an agent-based model to estimate how the costs and benefits of users in an online social network (OSN) impact the robustness of the OSN. Benefits are measured in terms of relative reputation that users receive from their followers. They can be increased by direct and indirect reciprocity in following each other, which leads to a core-periphery structure of the OSN. Costs relate to the effort to login, to maintain the profile, etc. and are assumed as constant for all users. The robustness of the OSN depends on the entry and exit of users over time. Intuitively, one would expect that higher costs lead to more users leaving and hence to a less robust OSN. We demonstrate that an optimal cost level exists, which maximizes both the performance of the OSN, measured by means of the long-term average benefit of its users, and the robustness of the OSN, measured by means of the lifetime of the core of the OSN. Our mathematical and computational analyses unfold how changes in the cost level impact reciprocity and subsequently the core-periphery structure of the OSN, to explain the optimal cost level.

Under what conditions do protests occur in civil wars? Evidence from case studies suggests that protests can indeed play an important role in contexts of civil wars, with civilians using respective tactics both against the state and rebels. We argue that localities experiencing armed clashes are likely to see protest events in the same month. Civilians conduct protests due to battle-related changes in the local opportunity structures and grievances related to losses experienced through collateral damage. Using spatially disaggregated data on protest and battle events in African civil wars, we find support for our hypothesis that battles trigger civilian protests. This effect is robust to the inclusion of a comprehensive list of confounding variables and alternative model specifications, including the use of different temporal and spatial units. Our findings highlight the role of the civilian population and the spatial relationship between war events and protests in civil wars.

It is well established that people often express emotions that are similar to those of other group members. However, people do not always express emotions that are similar to other group members, and the factors that determine when similarity occurs are not yet clear. In the current project, we examined whether certain situations activate specific emotional motives that influence the tendency to show emotional similarity. To test this possibility, we considered emotional responses to political situations that either called for weak (Studies 1 and 3) or strong (Study 2 and 4) negative emotions. Findings revealed that the motivation to feel weak emotions led people to be more influenced by weaker emotions than their own, whereas the motivation to feel strong emotions led people to be more influenced by stronger emotions than their own. Intriguingly, these motivations led people to change their emotions even after discovering that others’ emotions were similar to their initial emotional response. These findings are observed both in a lab task (Studies 1–3) and in real-life online interactions on Twitter (Study 4). Our findings enhance our ability to understand and predict emotional influence processes in different contexts and may therefore help explain how these processes unfold in group behavior.

Past studies on government survival in parliamentary democracies have been limited to national governments. However, most societies live in a multilevel polity where different policies are decided at distinct governmental layers. So far, the conditions triggering sub-national governments’ termination have remained unexplored. Our paper makes a twofold contribution to the literature. First, we explicitly focus our analysis on the sub-national government level. Second, we expand the analytical scope by assuming a multilevel setting, in which the survival of sub-national governments is dependent on both the party composition of the national government (vertical congruence) and their sub-national peers (horizontal congruence). We test the impact of both congruence measures on the early termination risk of regional governments. Our analysis is complemented by including “traditional” factors from national government termination literature, such as structural attributes of governments and their bargaining environment, into empirical modelling. Analysing a novel dataset on 494 regional governments in Germany and Spain we find that the risk of sub-national government termination is related to varying levels of vertical congruence. Furthermore, we find interesting explanatory variation between the two countries with regard to the effect size of economic performance, regional authority and congruence.

Because accountability may improve the comparability that is compromised by lenient grading, we compare exit exam outcomes in the same schools before and after a policy change that increased teacher accountability by anchoring grading scales through centralization. In particular, using a large administrative dataset of 364,445 exit exam outcomes for 72,889 students, we find that centralization increased inequality in scoring between the higher and lower performing schools by about 25%. In addition, the reform improved relative scoring outcomes for schools with larger shares of male students and lowered relative scoring outcomes for schools with a higher share of minority students.

We present a polling strategy to predict and analyze runoff elections using the 2017 French presidential race as an empirical case. This strategy employs rejective probability sampling to identify a small sample of polling stations that is balanced with respect to past election results. We then survey the voters’ candidate evaluations in first-round exit polls. We poststratify the voter sample to first-round election returns to account for nonresponse and coverage issues, and impute missing candidate evaluations to emulate campaign learning. Next, the votes for eliminated competitors are redistributed according to their supporters’ lower-order preferences. Finally, the predictions are validated against official results and other polls. We end with a discussion of the advantages and limitations of this approach.

Understanding the temporal dynamics of affect is crucial for our understanding human emotions in general. In this study, we empirically test a computational model of affective dynamics by analyzing a large-scale dataset of Facebook status updates using text analysis techniques. Our analyses support the central assumptions of our model: After stimulation, affective states, quantified as valence and arousal, exponentially return to an individual-specific baseline. On average, this baseline is at a slightly positive valence value and at a moderate arousal point below the midpoint. Furthermore, affective expression, in this case posting a status update on Facebook, immediately pushes arousal and valence towards the baseline by a proportional value. These results are robust to the choice of the text analysis technique and illustrate the fast timescale of affective dynamics through social media text. These outcomes are of high relevance for affective computing, the detection and modeling of collective emotions, the refinement of psychological research methodology, and the detection of abnormal, and potentially pathological, individual affect dynamics.