Jan Lorenz

This chapter describes academic events called “Summer School and Research Incubator”. They combine a lecture program with group project work, where lecturers and fellows collaborate on publication projects under a joint topical and methodological umbrella. This chapter reflects the experience of organizing five such events. It summarizes their benefits and the particular purposes of facilitating early academic independence, qualifying and enriching interdisciplinary research, and disseminating innovative research methods and topics.

The emergence of Computational Social Science (CSS) marks a transformative shift in the study of social phenomena, triggered by advancements in computational technology and large-scale collection of (digital) behavioral trace data. CSS promises to provide an accurate and deep understanding of social behavior through the analysis of social interactions, movement patterns, and communication networks at scale. However, the lack of a common theoretical language and clearly defined scientific agenda complicates CSS’ ability to build a common understanding of social phenomena. In this chapter, we establish CSS as a scientific paradigm, emphasizing the integration of computational tools with rigorous theoretical modeling. Specifically, we position CSS within the trajectory of a maturing science and emphasize the synthesis of data-driven CSS with theoretically-informed modeling for understanding social phenomena like social cohesion and polarization. To illustrate how CSS can advance these fields specifically, we unpack a range of conceptualizations of political polarization and social cohesion, and demonstrate how they have evolved in Europe over recent decades. Finally, we discuss how the subsequent chapters in this book aim to bridge the gap between theoretical and empirical CSS for social cohesion and polarization.

Why do some behaviours rapidly spread across society, while others fade despite widespread support? Theories of attitudes and social influence often provide competing explanations. We present an agent-based model that integrates three basic intuitions from social sciences: that behaviour is affected by individual dispositions, by social influence, and by one’s past behaviour. Simulating the joint dynamics of these three mechanisms shows that even small attitudinal preferences can determine society-level outcomes, and that all three mechanisms are required for this process to unfold. Our results reconceptualize the attitude-behaviour gap in dynamic terms and problematize the view of attitudes and conformity pressures as competing forces. The results provide a new look at the unexpected rise of behaviours that are disapproved by the majority, such as populist voting, climate denialism, and resistance to vaccination.

Political polarization represents a rising issue in many countries, making it more and more important to understand its relation to cognitive‐motivational and social influence mechanisms. Yet, the link between micro‐level mechanisms and macro‐level phenomena remains unclear. We investigated the consequences of individuals striving for cognitive coherence in their belief systems on political polarization in society in an agent‐based model. In this, we formalized how cognitive coherence affects how individuals update their beliefs following social influence and self‐reflection processes. We derive agents' political beliefs as well as their subjective belief systems, defining what determines coherence for different individuals, from European Social Survey data via correlational class analysis. The simulation shows that agents polarize in their beliefs when they have a strong strive for cognitive coherence, and especially when they have structurally different belief systems. In a mathematical analysis, we not only explain the main findings but also underscore the necessity of simulations for understanding the complex dynamics of socially embedded phenomena such as political polarization.

This paper offers a comparative perspective into the discourse of two online communities on the forum social media platform Reddit: r/antiwork, a group focused on the issues faced by workers with largely anti-capitalist sentiments, and r/TwoXchromosomes, a space for discussions of women’s struggles with anti-patriarchal views. We argue that these communities constitute a distinct digital form of political engagement and activism as resistance groups.using the concept of everyday resistance. That means using a set of small-scale, small-impact actions undertaken to contest power relations in a covert and unorganised manner. The data for this study comprises of 84,230 Reddit posts spanning 13 years and was analysed using topic models based on Latent Dirichlet Allocation (LDA). The findings demonstrate that discussions in both communities there are strong patterns of a collecitve social identity, despite the anonymous environment. The ways in which resistance is understood differs, with r/antiwork engaging in more radical and explicit discourses, and r/TwoXchromosomes being more focused on traditional activism, legal and political reform. Discussions in both spaces have a high degree of semantic similarity. Based on these results, we argue that social identity salience plays a crucial role in shaping discussions in online resistance communities. This finding is particularly valuable in the field of digital participation, by offering a lens through which online civic and political engagement can be better understood both as a medium of discussing resistance practices, and as a practice of everyday resistance itself.

Agent-based modeling and computer simulation is a research practice used to explore and explain the emergence of macroscopic phenomena of human societies. We are looking at five examples through a common lens. The examples are: the phenomena of ethnic segregation; the fate of street protests; the relations of redistribution, growth, and inequality; fragmentation and polarization of attitudes, and the evolution of filter bubbles. A special focus is put on the description of the generative mechanisms using simple models that can be used online and the distinction of mechanisms of type I (which govern the behavior of individuals and institutions) and type II (which govern the emergence of new systemic properties). Finally, five extensions of the simple models are discussed, which demonstrate different research directions that can be taken in exploring and developing social theory.

Agent-based models of opinion dynamics enable the investigation of societal phenomena that psychological theories of individual opinion change trigger in artificial societies. Many of such models are validated on the phenomenological level only (e.g., can they produce polarization) and not with respect to opinion data about real-world attitude distributions known from social surveys or individual attitude change observed in panel surveys. In this work, we use an existing agent-based model which builds on repeated random pairwise interaction as introduced in many early opinion dynamics models with a function of individual opinion change that includes the contagious and assimilating opinion adjustment, idiosyncratic opinion change, and motivated cognition, which is a generalization of the concept of bounded confidence. Depending on its parameters, this model creates different opinion distributions. By arguing that institutional trust is formed by an exchange of experiences and opinions, we then match the opinion distributions from the seven institutional trust questions in the European Social Survey to the simulated ones. Goodness-of-fit measures allow to calibrate the model parameters to reproduce 1,235 empirical distributions (for different countries and years) and further on, the calibration procedure is extended to data about individual opinion change from the Swiss Household Panel where participants reported their trust in the government on a yearly basis. Overall the opinion dynamics model reproduces most of the empirical distributions to a high degree, additionally, matching agents to individuals shows also a high level of concordance. In the analysis, we show that the concept of motivated cognition is a crucial part to achieve this level of accuracy. However, in both calibrations, we expose the shortcoming of the model to reproduce individuals with extreme and neutral attitudes.

In recent years, political discourse and election results appear to be more polarized in western countries but is this associated with increasing attitude polarization of their general public? To answer this question, many different polarization measures have been proposed in the literature but no systematic empirical comparison exists. In an exploratory analysis of 4155 attitude distributions on 11-point scales from the European Social Survey, we find that most polarization measures for single attitude distributions correlate strongly with the average attitude discrepancy between randomly selected pairs. We propose this as a catch-all measure for polarization because it can be decomposed into components related to different groups. By analyzing attitude distributions of the left–right political self-placements and several other topics, we find that distributions are typically not unimodal or bimodal, but show more so a structure with up to five modes. We exploit this structure by fitting a model with five latent groups of moderates, extremists, and centrists. Finally, we use the decomposition of polarization with respect to these groups to analyze polarization and its different aspects across topics, countries, and time establishing an overview and new perspectives on single attitude polarization in Europe.

While recent trends in the study of radial party voting have tended to focus on egalitarian attitudes and individual personality traits in their endeavor to explain radical party choice, the present study pits individual identity traits in the spotlight of ballot box behavior, using data from the World Values Survey and European Values Survey. We analyze the link between exclusive and inclusive identity (identifying with a more restricted ‘in-group’ versus identifying with a larger community) and the propensity to vote for radical right and radical left parties, using differences in individual identification with respondents’ home nation and as European citizens. The results show that exclusive individual identity is a good predictor of radical right party choice, even in the presence of redistributive and egalitarian values usually associated with left-wing voting. The results also speak to the literature on welfare chauvinism. While the presence of strong egalitarian and redistributive attitudes does indeed normally predict radical left party preference in line with previous findings, this relationship is complicated by the presence of exclusive individual identity, which moderates the former’s effect and can induce egalitarian voters to prefer radical right parties. In conclusion, the paper explores the interaction of identity and social class.