Peter Steiglechner

• Polarisation is a great concern in current social and political debates. A divergence of opinions or, more generally, a lack of societal agreement, for example on fundamental problems like climate change, presents a barrier to rapid action against a looming crisis. There are many theories on why people polarise on certain topics. However, the drivers of polarisation in social environments are multi-faceted and involve complex feedbacks among social, cognitive, and structural processes. While humans require interactions with each other to form shared views and cooperate effectively on many problems, social influence can produce a variety of opinion patterns, such as consensus, persistent disagreement, or polarisation. In this thesis, I develop mathematical models of opinion formation or perception to uncover the conditions underpinning the emergence of such patterns. I formalise how psychological factors distort the way individuals perceive others into a mathematical language and analyse how these perceptions affect the formation of consensus or the persistence of disagreement in a virtual society. The factors are: (1) noise, (2) bias, or (3) subjective perception. Taken together, the three studies demonstrate that these factors distorting people's perceptions or responses to social influence have a non-negligible and sometimes surprising impact on collective opinion patterns. This thesis highlights the importance to better understand the mechanisms behind social phenomena and their non-trivial consequences on opinion dynamics. While the models and the conclusions presented in the thesis may not be readily used to predict opinion patterns, owing to the complexity and inherent uncertainty of our society, they contribute to the social sciences by demonstrating counter-intuitive consequences of seemingly obvious theoretical assumptions, highlighting gaps and potentially critical ambiguities in social theories, and suggesting future directions for empirical analysis.