Opinion polarization and network segregation. Modelling a complex Relationship

Recently, many societies seem to shift towards more polarization and volatility in opinions, for example in attitudes about immigration, climate policy, or the best policy response to Covid-19. A key obstacle for a scientific understanding of this development is that opinion dynamics in society involve a complex micro-macro interaction between processes of social influence occurring at the micro-level, meso-level conditions like network structures, and macro-level outcomes, like consensus, opinion-clustering or polarization. I will discuss how agent-based simulation models (ABM) can be used to further our understanding how micro-level processes relate to macro-level dynamics in opinion formation. Computational agent-based models will be presented that highlight alternative and competing theoretical  perspectives, some suggesting that network segregation between different groups fosters polarizations, other pointing to the opposite possibility. I will also discuss how empirical research using experiments and social network data can help to test model implications.